context("computeBounds") source(system.file("tests/comparisons/indices.R", package = "stepR")) source(system.file("tests/comparisons/singleStat.R", package = "stepR")) source(system.file("tests/comparisons/singleBounds.R", package = "stepR")) # indices testIndices <- function(bounds, indices, ...) { compareIndices <- as.data.frame(indices(...)) compareIndices <- compareIndices[order(compareIndices$ri, compareIndices$li, decreasing = FALSE), ] bounds <- bounds[order(bounds$ri, bounds$li, decreasing = FALSE), ] expect_identical(bounds$li, compareIndices$li) expect_identical(bounds$ri, compareIndices$ri) } # bounds testBounds <- function(bounds, singleBounds, tolerance = 1e-10, y, criticalValues, lengths = 1:length(y), ...) { for (i in 1:length(bounds$li)) { compareBounds <- singleBounds(y, criticalValues[lengths == bounds$ri[i] - bounds$li[i] + 1L], bounds$li[i], bounds$ri[i], ...) expect_equal(c(bounds$lower[i], bounds$upper[i]), compareBounds, tolerance = tolerance, info = i) } } # bounds via statistic == criticalValue testStat <- function(bounds, singleStat, tolerance = 1e-6, y, criticalValues, lengths = 1:length(y), ...) { for (i in 1:length(bounds$li)) { compareStats <- c(singleStat(y, bounds$lower[i], bounds$li[i], bounds$ri[i], ...), singleStat(y, bounds$lower[i], bounds$li[i], bounds$ri[i], ...)) expect_equal(compareStats, rep(criticalValues[lengths == bounds$ri[i] - bounds$li[i] + 1L], 2), tolerance = tolerance, info = i) } } test_that("argument y is tested", { testn <- 40L testy <- rnorm(testn) testq <- rep(1, testn) expect_error(computeBounds(q = testq)) expect_error(computeBounds(numeric(0), q = testq)) expect_identical(computeBounds(testy, q = testq), computeBounds(testy, family = "gauss", intervalSystem = "all", lengths = 1:testn, q = testq, sd = sdrobnorm(testy))) expect_error(computeBounds(as.integer(testy), q = testq)) expect_error(computeBounds(c(testy, "s"), q = testq)) expect_error(computeBounds(c(rnorm(10), NA), q = testq)) bounds <- computeBounds(testy, q = testq, sd = 1) testIndices(bounds = bounds, indices = indicesAll, n = testn) testBounds(bounds = bounds, singleBounds = singleBoundsGauss, y = testy, criticalValues = testq, sd = 1) testStat(bounds = bounds, singleStat = singleStatGauss, y = testy, criticalValues = testq, sd = 1) }) test_that("argument family is tested and works in the default case", { # other families below testn <- 53L testy <- c(rnorm(30, 1, 0.23), rnorm(testn - 30, -1, 0.34)) testq <- 53:1 / 20 expect_error(computeBounds(testy, family = "", q = testq)) expect_error(computeBounds(testy, family = c("gauss", "hsmuce"), q = testq)) expect_identical(computeBounds(testy, q = testq), computeBounds(testy, q = testq, family = "gauss")) bounds <- computeBounds(testy, q = testq, sd = 0.3) testIndices(bounds = bounds, indices = indicesAll, n = testn) testBounds(bounds = bounds, singleBounds = singleBoundsGauss, y = testy, criticalValues = testq, sd = 0.3) testStat(bounds = bounds, singleStat = singleStatGauss, y = testy, criticalValues = testq, sd = 0.3) }) test_that("argument intervalSystem is tested and works", { testn <- 23L testy <- c(rnorm(10, 1, 0.23), rnorm(testn - 10, -1, 0.34)) testq <- 23:1 / 10 expect_error(computeBounds(testy, intervalSystem = "", q = testq)) expect_error(computeBounds(testy, intervalSystem = "dya", q = testq)) expect_error(computeBounds(testy, intervalSystem = "dyalen", q = testq)) expect_error(computeBounds(testy, intervalSystem = "dyapar", q = testq)) expect_identical(computeBounds(testy, q = testq), computeBounds(testy, q = testq, intervalSystem = "all")) testq <- 5:1 / 5 bounds <- computeBounds(testy, q = testq, intervalSystem = "dyaLen", sd = 0.3) testIndices(bounds = bounds, indices = indicesDyaLen, n = testn) testBounds(bounds = bounds, singleBounds = singleBoundsGauss, y = testy, criticalValues = testq, lengths = 2^(0:4), sd = 0.3) testStat(bounds = bounds, singleStat = singleStatGauss, y = testy, criticalValues = testq, lengths = 2^(0:4), sd = 0.3) bounds <- computeBounds(testy, q = testq, intervalSystem = "dyaPar", sd = 0.3) testIndices(bounds = bounds, indices = indicesDyaPar, n = testn) testBounds(bounds = bounds, singleBounds = singleBoundsGauss, y = testy, criticalValues = testq, lengths = 2^(0:4), sd = 0.3) testStat(bounds = bounds, singleStat = singleStatGauss, y = testy, criticalValues = testq, lengths = 2^(0:4), sd = 0.3) }) test_that("argument lengths is tested and works", { testn <- 37L testy <- c(rnorm(20, 1, 0.23), rnorm(testn - 20, -1, 0.34)) testq <- 37:1 / 12 expect_error(computeBounds(testy, lengths = "s", q = testq)) expect_error(computeBounds(testy, lengths = c(1:10, NA), q = testq)) expect_error(computeBounds(testy, lengths = c(1:10, Inf), q = testq)) expect_error(computeBounds(testy, lengths = 0:10, q = testq)) expect_error(computeBounds(testy, lengths = -1L, q = testq)) expect_error(computeBounds(testy, lengths = 38L, q = testq)) expect_warning(ret <- computeBounds(testy, lengths = c(1:10, 10), q = testq)) expect_identical(ret, computeBounds(testy, lengths = c(1:10), q = testq)) expect_identical(computeBounds(testy, lengths = c(10:1), q = testq), computeBounds(testy, lengths = c(1:10), q = testq)) expect_identical(computeBounds(testy, lengths = c(1:10 + 0.5), q = testq), computeBounds(testy, lengths = c(1:10), q = testq)) testq <- 2 expect_error(computeBounds(testy, intervalSystem = "dyaLen", lengths = 3L, q = testq)) expect_error(computeBounds(testy, intervalSystem = "dyaLen", lengths = 64L, q = testq)) expect_error(computeBounds(testy, intervalSystem = "dyaPar", lengths = 3L, q = testq)) expect_error(computeBounds(testy, intervalSystem = "dyaPar", lengths = 64L, q = testq)) testq <- 9:1 bounds <- computeBounds(testy, q = testq, lengths = c(2, 5:10, 35:36), sd = 0.3) testIndices(bounds = bounds, indices = indicesAllLengths, n = testn, lengths = c(2, 5:10, 35:36)) testBounds(bounds = bounds, singleBounds = singleBoundsGauss, y = testy, criticalValues = testq, lengths = c(2, 5:10, 35:36), sd = 0.3) testStat(bounds = bounds, singleStat = singleStatGauss, y = testy, criticalValues = testq, lengths = c(2, 5:10, 35:36), sd = 0.3) testq <- 3:1 / 5 bounds <- computeBounds(testy, q = testq, intervalSystem = "dyaLen", lengths = c(1, 4, 32), sd = 0.3) testIndices(bounds = bounds, indices = indicesDyaLenLengths, n = testn, lengths = c(1, 4, 32)) testBounds(bounds = bounds, singleBounds = singleBoundsGauss, y = testy, criticalValues = testq, lengths = c(1, 4, 32), sd = 0.3) testStat(bounds = bounds, singleStat = singleStatGauss, y = testy, criticalValues = testq, lengths = c(1, 4, 32), sd = 0.3) testq <- 2:1 / 5 bounds <- computeBounds(testy, q = testq, intervalSystem = "dyaPar", sd = 0.3, lengths = c(2, 4)) testIndices(bounds = bounds, indices = indicesDyaParLengths, n = testn, lengths = c(2, 4)) testBounds(bounds = bounds, singleBounds = singleBoundsGauss, y = testy, criticalValues = testq, lengths = c(2, 4), sd = 0.3) testStat(bounds = bounds, singleStat = singleStatGauss, y = testy, criticalValues = testq, lengths = c(2, 4), sd = 0.3) }) test_that("argument q is tested and works if it is given", { testn <- 36L testy <- c(rnorm(12, 1, 0.23), rnorm(12, -1, 0.23), rnorm(12, 1, 0.23)) teststat <- monteCarloSimulation(36L, r = 100L) expect_warning(ret <- computeBounds(testy)) expect_identical(ret, computeBounds(testy, alpha = 0.5)) expect_warning(ret <- computeBounds(testy, stat = teststat)) expect_identical(ret, computeBounds(testy, stat = teststat, alpha = 0.5)) expect_error(computeBounds(testy, q = "s", alpha = 0.1, stat = teststat)) expect_error(computeBounds(testy, q = Inf, alpha = 0.1, stat = teststat)) expect_error(computeBounds(testy, q = c(rep(1, 35), "s"), alpha = 0.1, stat = teststat)) expect_error(computeBounds(testy, q = c(rep(1, 35), Inf), alpha = 0.1, stat = teststat)) expect_error(computeBounds(testy, q = rep(1, 37), alpha = 0.1, stat = teststat)) expect_error(computeBounds(testy, q = rep(1, 33), alpha = 0.1, stat = teststat)) testq <- 1:36 attr(testq, "n") <- "s" expect_error(computeBounds(testy, q = testq, alpha = 0.1, stat = teststat)) attr(testq, "n") <- 35L expect_error(computeBounds(testy, q = testq, alpha = 0.1, stat = teststat)) expect_identical(computeBounds(testy, q = 3, intervalSystem = "all", lengths = c(1:3, 8:23)), computeBounds(testy, intervalSystem = "all", lengths = c(1:3, 8:23), q = critVal(q = 3, intervalSystem = "all", lengths = c(1:3, 8:23), n = testn))) expect_identical(computeBounds(testy, q = 3, intervalSystem = "dyaLen", lengths = c(1, 4, 8, 32), nq = 45L), computeBounds(testy, intervalSystem = "dyaLen", lengths = c(1, 4, 8, 32), q = critVal(q = 3, intervalSystem = "dyaLen", lengths = c(1, 4, 8, 32), n = testn, nq = 45L))) expect_identical(computeBounds(testy, q = 3, intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32)), computeBounds(testy, intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32), q = critVal(q = 3, intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32), n = testn))) testq <- 1:45 attr(testq, "n") <- 45L expect_identical(computeBounds(testy, q = testq), computeBounds(testy, q = 1:36)) expect_identical(computeBounds(testy, q = 1:36, lengths = 3:23), computeBounds(testy, q = 3:23, lengths = 3:23)) expect_identical(computeBounds(testy, q = testq, lengths = 3:23), computeBounds(testy, q = 3:23, lengths = 3:23)) expect_identical(computeBounds(testy, q = 1:36, intervalSystem = "dyaLen"), computeBounds(testy, q = 2^(0:5), intervalSystem = "dyaLen")) expect_identical(computeBounds(testy, q = testq, intervalSystem = "dyaLen"), computeBounds(testy, q = 2^(0:5), intervalSystem = "dyaLen")) testq <- 2^(0:6) attr(testq, "n") <- 64L expect_identical(computeBounds(testy, q = testq, intervalSystem = "dyaPar"), computeBounds(testy, q = 2^(0:5), intervalSystem = "dyaPar")) }) test_that("argument q is computed correctly", { testn <- 36L testy <- c(rnorm(12, 1, 0.23), rnorm(12, -1, 0.23), rnorm(12, 1, 0.23)) teststat <- monteCarloSimulation(36L, r = 100L) ret <- computeBounds(testy, alpha = 0.1, stat = teststat) expect_identical(ret, computeBounds(testy, alpha = 0.1, stat = teststat, nq = testn, family = "gauss", intervalSystem = "all", lengths = 1:testn, penalty = "sqrt")) expect_identical(ret, computeBounds(testy, q = critVal(alpha = 0.1, stat = teststat, n = testn))) expect_error(computeBounds(testy, alpha = "s", stat = teststat)) expect_error(computeBounds(testy, alpha = 0, stat = teststat)) expect_identical(computeBounds(testy, alpha = 0.075, stat = teststat), computeBounds(testy, q = critVal(alpha = 0.075, stat = teststat, n = testn))) expect_error(computeBounds(testy, alpha = 0.1, stat = teststat, n = testn)) expect_error(computeBounds(testy, alpha = 0.1, nq = "s", stat = teststat)) expect_error(computeBounds(testy, q = 1, nq = "s", stat = teststat)) expect_error(computeBounds(testy, alpha = 0.1, nq = Inf, stat = teststat)) expect_error(computeBounds(testy, q = 1, nq = Inf, stat = teststat)) expect_error(computeBounds(testy, alpha = 0.1, nq = 8L, stat = teststat)) expect_error(computeBounds(testy, q = 1, nq = 8L, stat = teststat)) expect_error(computeBounds(testy, alpha = 0.1, penalty = "", stat = teststat)) expect_error(computeBounds(testy, alpha = 0.1, penalty = "ads", stat = teststat)) expect_error(computeBounds(testy, alpha = 0.1, penalty = "weights", weights = rep(1 / 8, 8), stat = teststat)) expect_identical(computeBounds(testy, alpha = 0.1, penalty = "weights", stat = teststat), computeBounds(testy, q = critVal(alpha = 0.1, penalty = "weights", weights = rep(1 / 36, 36), stat = teststat, n = testn))) expect_identical(computeBounds(testy, alpha = 0.1, penalty = "weights", weights = rep(1, 36), stat = teststat), computeBounds(testy, q = critVal(alpha = 0.1, penalty = "weights", weights = rep(1 / 36, 36), stat = teststat, n = testn))) teststat <- monteCarloSimulation(n = 36L, r = 100L) expect_identical(computeBounds(testy, alpha = 0.14, penalty = "log", stat = teststat, intervalSystem = "all", lengths = c(1, 5, 8, 23)), computeBounds(testy, intervalSystem = "all", lengths = c(1, 5, 8, 23), q = critVal(alpha = 0.14, intervalSystem = "all", lengths = c(1, 5, 8, 23), penalty = "log", stat = teststat, n = testn))) teststat <- monteCarloSimulation(n = 36L, r = 100L, intervalSystem = "dyaLen") expect_identical(computeBounds(testy, alpha = 0.034, penalty = "none", stat = teststat, intervalSystem = "dyaLen", lengths = c(1, 4, 8, 32)), computeBounds(testy, intervalSystem = "dyaLen", lengths = c(1, 4, 8, 32), q = critVal(alpha = 0.034, intervalSystem = "dyaLen", lengths = c(1, 4, 8, 32), penalty = "none", stat = teststat, n = testn))) teststat <- monteCarloSimulation(n = 36L, r = 100L, intervalSystem = "dyaPar") expect_identical(computeBounds(testy, alpha = 0.56, penalty = "weights", weights = c(0.2, 0.3, 0.4, 0.1), stat = teststat, intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32)), computeBounds(testy, intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32), q = critVal(alpha = 0.56, intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32), penalty = "weights", weights = c(0.2, 0.3, 0.4, 0.1), stat = teststat, n = testn))) teststat <- matrix(abs(rnorm(1e4 * testn)), testn, 1e4) expect_error(computeBounds(testy, alpha = 0.1, stat = teststat)) teststat <- monteCarloSimulation(n = 37L, r = 100L) expect_identical(computeBounds(testy, alpha = 0.05, stat = teststat, nq = 37L), computeBounds(testy, q = critVal(alpha = 0.05, stat = teststat, n = testn, nq = 37L))) teststat <- monteCarloSimulation(n = 36L, r = 100L, intervalSystem = "dyaPar") expect_identical(computeBounds(testy, alpha = 0.014, stat = teststat, nq = 100L, intervalSystem = "dyaPar", lengths = 2^c(0:3, 5)), computeBounds(testy, intervalSystem = "dyaPar", lengths = 2^c(0:3, 5), q = critVal(alpha = 0.014, intervalSystem = "dyaPar", lengths = 2^c(0:3, 5), stat = teststat, n = testn, nq = 100L))) teststat <- monteCarloSimulation(n = 36L, r = 100L, intervalSystem = "all") expect_identical(computeBounds(testy, alpha = 0.014, stat = teststat, nq = 100L, intervalSystem = "all", lengths = 1L), computeBounds(testy, intervalSystem = "all", lengths = 1L, q = critVal(alpha = 0.014, intervalSystem = "all", lengths = 1L, stat = teststat, n = testn, nq = 100L))) expect_error(computeBounds(testy, alpha = 0.1, output = "vector", stat = teststat)) expect_error(computeBounds(testy, alpha = 0.1, data = 1, stat = teststat)) teststat <- monteCarloSimulation(n = 36L, r = 100L, output = "maximum") expect_error(computeBounds(testy, alpha = 0.1, penalty = "weights", stat = teststat)) teststatmatrix <- monteCarloSimulation(n = 36L, r = 100L) teststatvector <- monteCarloSimulation(n = 36L, r = 100L, output = "maximum", penalty = "sqrt") expect_identical(computeBounds(testy, alpha = 0.05, stat = teststatvector), computeBounds(testy, q = critVal(alpha = 0.05, stat = teststatmatrix, n = testn))) teststatvector <- monteCarloSimulation(n = 36L, r = 100L, output = "maximum", penalty = "log", lengths = c(1, 3, 5, 8, 9, 12)) expect_identical(computeBounds(testy, alpha = 0.15, stat = teststatvector, nq = 100L, lengths = c(1, 3, 5, 8, 9, 12), penalty = "log"), computeBounds(testy, lengths = c(1, 3, 5, 8, 9, 12), q = critVal(alpha = 0.15, stat = teststatmatrix, n = testn, nq = 100L, lengths = c(1, 3, 5, 8, 9, 12), penalty = "log"))) teststatmatrix <- monteCarloSimulation(n = 36L, r = 100L, intervalSystem = "dyaLen") teststatvector <- monteCarloSimulation(n = 36L, r = 100L, output = "maximum", intervalSystem = "dyaLen", penalty = "sqrt", lengths = c(1, 2, 8, 16)) expect_identical(computeBounds(testy, alpha = 0.05, stat = teststatvector, nq = 2^7L, intervalSystem = "dyaLen", lengths = c(1, 2, 8, 16), penalty = "sqrt"), computeBounds(testy, intervalSystem = "dyaLen", lengths = c(1, 2, 8, 16), q = critVal(alpha = 0.05, stat = teststatmatrix, n = testn, nq = 2^7L, intervalSystem = "dyaLen", lengths = c(1, 2, 8, 16), penalty = "sqrt"))) teststatmatrix <- monteCarloSimulation(n = 36L, r = 100L, intervalSystem = "dyaPar") teststatvector <- monteCarloSimulation(n = 36L, r = 100L, output = "maximum", intervalSystem = "dyaPar", penalty = "sqrt", lengths = c(1, 2, 8, 16, 32)) expect_identical(computeBounds(testy, alpha = 0.122, stat = teststatvector, nq = 2^9L, intervalSystem = "dyaPar", lengths = c(1, 2, 8, 16, 32), penalty = "sqrt"), computeBounds(testy, intervalSystem = "dyaPar", lengths = c(1, 2, 8, 16, 32), q = critVal(alpha = 0.122, stat = teststatmatrix, n = testn, nq = 2^9L, intervalSystem = "dyaPar", lengths = c(1, 2, 8, 16, 32), penalty = "sqrt"))) expect_identical(computeBounds(testy, alpha = 0.122, stat = teststatvector, nq = 2^9L, intervalSystem = "dyaPar", lengths = c(1, 2, 8, 16, 32), penalty = "sqrt"), computeBounds(testy, intervalSystem = "dyaPar", lengths = c(1, 2, 8, 16, 32), q = critVal(alpha = 0.122, stat = teststatvector, n = testn, nq = 2^9L, intervalSystem = "dyaPar", lengths = c(1, 2, 8, 16, 32), penalty = "sqrt", output = "vector"))) expect_identical(computeBounds(testy, alpha = 0.122, stat = teststatvector, nq = 2^9L, intervalSystem = "dyaPar", lengths = c(1, 2, 8, 16, 32), penalty = "sqrt"), computeBounds(testy, intervalSystem = "dyaPar", lengths = c(1, 2, 8, 16, 32), q = critVal(alpha = 0.122, stat = teststatmatrix, n = testn, nq = 2^9L, intervalSystem = "dyaPar", lengths = c(1, 2, 8, 16, 32), penalty = "sqrt", output = "vector"))) expect_error(computeBounds(testy, alpha = 0.1, r = "s", options = list(load = list()))) expect_error(computeBounds(testy, alpha = 0.1, r = 0, options = list(load = list()))) expect_error(computeBounds(testy, alpha = 0.1, r = c(100, 200), options = list(load = list()))) expect_identical(computeBounds(testy, alpha = 0.1, r = 100.5, options = list(load = list())), computeBounds(testy, alpha = 0.1, r = 100L, options = list(load = list()))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulat = "vector", save = list(), load = list()))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = "vector")) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "vecto", save = list(), load = list()))) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, intervalSystem = "dyaPar", lengths = c(2, 4, 8), penalty = "log", options = list(simulation = "vector", save = list(), load = list())), computeBounds(testy, intervalSystem = "dyaPar", lengths = c(2, 4, 8), q = critVal(n = length(testy), alpha = 0.1, r = 100L, intervalSystem = "dyaPar", lengths = c(2, 4, 8), penalty = "log", options = list(simulation = "vector", save = list(), load = list())))) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, lengths = 3:17, penalty = "log", options = list(simulation = "vectorIncreased", save = list(), load = list())), computeBounds(testy, lengths = 3:17, q = critVal(n = length(testy), alpha = 0.1, r = 100L, lengths = 3:17, penalty = "log", options = list(simulation = "vectorIncreased", save = list(), load = list())))) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, lengths = 3:17, penalty = "log", nq = 100, options = list(simulation = "vectorIncreased", save = list(), load = list())), computeBounds(testy, lengths = 3:17, q = critVal(n = 100, alpha = 0.1, r = 100L, lengths = 3:17, penalty = "log", options = list(simulation = "vector", save = list(), load = list())))) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, lengths = 10:13, penalty = "weights", weights = rep(1 / 4, 4), options = list(simulation = "matrix", save = list(), load = list())), computeBounds(testy, lengths = 10:13, q = critVal(n = length(testy), alpha = 0.1, r = 100L, lengths = 10:13, penalty = "weights", weights = rep(1 / 4, 4), options = list(simulation = "matrix", save = list(), load = list())))) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "matrixIncreased", save = list(), load = list())), computeBounds(testy, q = critVal(n = length(testy), alpha = 0.1, r = 100L, options = list(simulation = "matrixIncreased", save = list(), load = list())))) testfile <- c(tempfile(pattern = "file", tmpdir = tempdir(), fileext = ".RDS"), tempfile(pattern = "file", tmpdir = tempdir(), fileext = ".RDS")) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "vector", save = list(RDSfile = testfile, test = 1), load = list()))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "vector", save = list(RDSfile = testfile), load = list(test = "test")))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "vector", save = list(RDSfile = c(testfile, testfile)), load = list()))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "vector", save = list(RDSfile = 10), load = list()))) teststat <- monteCarloSimulation(36L, r = 100L) teststatvec <- monteCarloSimulation(36L, r = 100L, output = "maximum") expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "matrix", save = list(RDSfile = testfile), load = list())), computeBounds(testy, alpha = 0.1, stat = teststat)) expect_identical(readRDS(testfile[1]), teststatvec) expect_identical(readRDS(testfile[2]), teststat) expect_error(critVal(100L, alpha = 0.1, r = 100L, options = list(simulation = "vector", load = list(RDSfile = 10), save = list()))) expect_error(critVal(100L, alpha = 0.1, r = 100L, options = list(simulation = "vector", load = list(RDSfile = testfile), save = list()))) expect_identical(computeBounds(testy, alpha = 0.1, r = 50L, options = list(simulation = "matrix", load = list(RDSfile = testfile[1]), save = list())), computeBounds(testy, alpha = 0.1, stat = teststat)) expect_identical(computeBounds(testy, alpha = 0.1, r = 50L, options = list(simulation = "matrix", load = list(RDSfile = testfile[1]), save = list())), computeBounds(testy, alpha = 0.1, stat = teststat)) unlink(testfile) testvariable <- c("testsavevector", "testsavematrix") testStepR <- new.env() expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "vector", save = list(variable = c(testvariable, testvariable)), load = list(), envir = testStepR))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "vector", save = list(variable = 10), load = list(), envir = testStepR))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "vector", save = list(variable = testvariable), load = list(), envir = "testStepR"))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "vector", save = list(variable = testvariable), load = list(), envir = c(testStepR, testStepR)))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "vector", save = list(variable = testvariable), load = list(), envir = c(testStepR, 10)))) teststat <- monteCarloSimulation(36L, r = 100L, output = "maximum") expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "vector", save = list(variable = testvariable), load = list(), envir = testStepR)), computeBounds(testy, alpha = 0.1, stat = teststat)) expect_identical(get("testsavevector", envir = testStepR), teststat) expect_false(exists("testsavematrix", envir = testStepR)) remove(testsavevector, envir = testStepR) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "matrix", save = list(workspace = "matri"), load = list(), envir = testStepR))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "matrix", save = list(workspace = c("vector", "matri")), load = list(), envir = testStepR))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "matrix", load = list(workspace = "matri"), save = list(), envir = testStepR))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "matrix", load = list(workspace = c("vector", "matri")), save = list(), envir = testStepR))) teststat <- monteCarloSimulation(36L, r = 100L) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "matrix", save = list(workspace = "matrix"), load = list(), envir = testStepR)), computeBounds(testy, alpha = 0.1, stat = teststat, options = list())) expect_identical(get("critValStepRTab", envir = testStepR, inherits = FALSE)$stat[[1]], teststat) expect_identical(length(get("critValStepRTab", envir = testStepR, inherits = FALSE)$stat), 1L) expect_identical(computeBounds(testy, alpha = 0.1, r = 50L, options = list(simulation = "matrix", save = list(), load = list(workspace = "matrix"), envir = testStepR)), computeBounds(testy, alpha = 0.1, stat = teststat, options = list())) remove(critValStepRTab, envir = testStepR) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "matrix", save = list(fileSystem = "matri"), load = list(), dirs = "testStepR"))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "matrix", save = list(fileSystem = c("vector", "matri")), load = list(), dirs = "testStepR"))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "matrix", load = list(fileSystem = "matri"), save = list(), dirs = "testStepR"))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "matrix", load = list(fileSystem = c("vector", "matri")), save = list(), dirs = "testStepR"))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "matrix", save = list(fileSystem = "matrix"), load = list(), dirs = c("testStepR", "test")))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "matrix", save = list(fileSystem = "matrix"), load = list(), dirs = 10))) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, options = list(simulation = "matrix", save = list(fileSystem = "matrix"), load = list(), dirs = "testStepR")), computeBounds(testy, alpha = 0.1, stat = teststat, options = list())) expect_identical(R.cache::loadCache(attr(teststat, "keyList"), dirs = "testStepR"), teststat) expect_identical(length(list.files(file.path(R.cache::getCacheRootPath(), "testStepR"))), 1L) expect_identical(critVal(36L, alpha = 0.1, r = 50L, options = list(simulation = "matrix", save = list(), load = list(fileSystem = "matrix"), dirs = "testStepR")), critVal(36L, alpha = 0.1, stat = teststat, options = list())) expect_identical(computeBounds(testy, alpha = 0.1, r = 50L, options = list(simulation = "matrix", save = list(), load = list(fileSystem = "matrix"), dirs = "testStepR")), computeBounds(testy, alpha = 0.1, stat = teststat, options = list())) unlink(file.path(R.cache::getCacheRootPath(), "testStepR"), recursive = TRUE) teststat1 <- monteCarloSimulation(36L, r = 100L, output = "maximum", lengths = c(23:34)) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, lengths = c(23:34), options = list(simulation = "vector", save = list(workspace = c("matrixIncreased", "vector", "matrix"), fileSystem = c("matrixIncreased", "vector", "matrix"), RDSfile = testfile, variable = testvariable), load = list(), envir = testStepR, dirs = "testStepR")), computeBounds(testy, alpha = 0.1, stat = teststat1, lengths = c(23:34), options = list())) expect_identical(readRDS(testfile[1]), teststat1) expect_false(file.exists(testfile[2])) expect_identical(get("testsavevector", envir = testStepR), teststat1) expect_false(exists("testsavematrix", envir = testStepR)) teststat2 <- monteCarloSimulation(36L, r = 100L, intervalSystem = "dyaPar") teststat3 <- monteCarloSimulation(36L, r = 100L, output = "maximum", intervalSystem = "dyaPar", lengths = 2^(1:3)) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, intervalSystem = "dyaPar", lengths = 2^(1:3), options = list(simulation = "matrix", save = list(workspace = c("vectorIncreased", "vector"), fileSystem = c("matrixIncreased", "matrix"), RDSfile = testfile, variable = testvariable), load = list(), envir = testStepR, dirs = "testStepR")), computeBounds(testy, alpha = 0.1, stat = teststat2, intervalSystem = "dyaPar", lengths = 2^(1:3), options = list())) expect_identical(readRDS(testfile[1]), teststat3) expect_identical(readRDS(testfile[2]), teststat2) expect_identical(get("testsavevector", envir = testStepR), teststat3) expect_identical(get("testsavematrix", envir = testStepR), teststat2) unlink(testfile) remove(testsavevector, envir = testStepR) remove(testsavematrix, envir = testStepR) teststat <- monteCarloSimulation(63L, r = 100L) teststat4 <- monteCarloSimulation(63L, r = 100L, output = "maximum", lengths = 1:36, penalty = "log") expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, stat = teststat, penalty = "log", options = list(simulation = "matrixIncreased", save = list(workspace = c("matrix", "vectorIncreased"), fileSystem = c("vector", "matrix")), load = list(workspace = c("vectorIncreased", "matrix")), envir = testStepR, dirs = "testStepR")), computeBounds(testy, alpha = 0.1, stat = teststat, penalty = "log", options = list())) teststat1new <- monteCarloSimulation(36L, r = 200L, output = "maximum", lengths = c(23:34)) expect_identical(critVal(36L, alpha = 0.1, r = 200L, output = "value", lengths = c(23:34), options = list(simulation = "vector", save = list(workspace = c("matrixIncreased", "vector", "matrix")), load = list(workspace = c("vector", "matrix")), envir = testStepR, dirs = "testStepR")), critVal(36L, alpha = 0.1, stat = teststat1new, output = "value", lengths = c(23:34), options = list())) expect_identical(computeBounds(testy, alpha = 0.1, r = 50L, penalty = "log", options = list(simulation = "matrix", save = list(fileSystem = c("matrix", "vectorIncreased")), load = list(workspace = c("vectorIncreased", "matrix")), envir = testStepR, dirs = "testStepR")), computeBounds(testy, alpha = 0.1, stat = teststat4, penalty = "log", options = list())) teststat5 <- monteCarloSimulation(36L, r = 100L, output = "maximum", intervalSystem = "dyaLen", lengths = 16L, penalty = "log") expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, intervalSystem = "dyaLen", lengths = 16L, penalty = "log", stat = teststat5, options = list(simulation = "vector", save = list(fileSystem = c("matrix", "vector"), workspace = c("matrix", "matrixIncreased")), load = list(workspace = c("vectorIncreased", "matrix")), envir = testStepR, dirs = "testStepR")), computeBounds(testy, alpha = 0.1, stat = teststat5, intervalSystem = "dyaLen", lengths = 16L, penalty = "log", options = list())) teststat6 <- monteCarloSimulation(125L, r = 100L, intervalSystem = "dyaLen") expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, penalty = "weights", nq = 125L, weights = 1:6 / sum(1:6), intervalSystem = "dyaLen", options = list(simulation = "matrixIncreased", save = list(workspace = c("matrixIncreased", "vector"), fileSystem = c("matrix", "vectorIncreased")), load = list(workspace = c("vectorIncreased", "matrix")), envir = testStepR, dirs = "testStepR")), computeBounds(testy, alpha = 0.1, stat = teststat6, penalty = "weights", weights = 1:6 / sum(1:6), intervalSystem = "dyaLen", options = list())) teststat6b <- monteCarloSimulation(125L, r = 100L, output = "maximum", penalty = "log", intervalSystem = "dyaLen", lengths = 2^(2:4)) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, penalty = "log", intervalSystem = "dyaLen", lengths = 2^(2:4), nq = 125L, options = list(simulation = "matrix", save = list(workspace = c("matrixIncreased", "vector"), fileSystem = c("matrix", "vectorIncreased")), load = list(workspace = c("matrixIncreased", "matrix")), envir = testStepR, dirs = "testStepR")), computeBounds(testy, alpha = 0.1, stat = teststat6, penalty = "log", intervalSystem = "dyaLen", lengths = 2^(2:4), options = list())) teststat <- monteCarloSimulation(36L, r = 200L, output = "maximum", rand.gen = function(data) {rnorm(36)}) expect_identical(computeBounds(testy, alpha = 0.1, r = 200L, rand.gen = function(data) {rnorm(36)}, options = list(simulation = "vector", save = list(workspace = c("matrix", "vector")), load = list(fileSystem = c("vectorIncreased", "matrix")), envir = testStepR, dirs = "testStepR")), computeBounds(testy, alpha = 0.1, stat = teststat, options = list())) teststat7 <- monteCarloSimulation(125L, r = 100L, output = "maximum", intervalSystem = "dyaLen", lengths = 2^(3:5), penalty = "log") expect_identical(critVal(120L, alpha = 0.1, r = 100L, output = "value", intervalSystem = "dyaLen", lengths = 2^(3:5), penalty = "log", nq = 125L, options = list(simulation = "vectorIncreased", save = list(workspace = c("matrixIncreased", "vectorIncreased")), load = list(workspace = c("matrix", "vector"), fileSystem = c("vectorIncreased", "matrixIncreased")), envir = testStepR, dirs = "testStepR")), critVal(120L, alpha = 0.1, stat = teststat7, output = "value", options = list(), intervalSystem = "dyaLen", lengths = 2^(3:5), penalty = "log")) expect_identical(length(get("critValStepRTab", envir = testStepR, inherits = FALSE)$stat), 5L) expect_identical(get("critValStepRTab", envir = testStepR, inherits = FALSE)$stat[[1]], teststat1new) expect_identical(get("critValStepRTab", envir = testStepR, inherits = FALSE)$stat[[2]], teststat3) expect_identical(get("critValStepRTab", envir = testStepR, inherits = FALSE)$stat[[3]], teststat4) expect_identical(get("critValStepRTab", envir = testStepR, inherits = FALSE)$stat[[4]], teststat6) expect_identical(get("critValStepRTab", envir = testStepR, inherits = FALSE)$stat[[5]], teststat7) remove(critValStepRTab, envir = testStepR) expect_identical(length(list.files(file.path(R.cache::getCacheRootPath(), "testStepR"))), 5L) expect_identical(R.cache::loadCache(attr(teststat1, "keyList"), dirs = "testStepR"), teststat1) expect_identical(R.cache::loadCache(attr(teststat2, "keyList"), dirs = "testStepR"), teststat2) expect_identical(R.cache::loadCache(attr(teststat4, "keyList"), dirs = "testStepR"), teststat4) expect_identical(R.cache::loadCache(attr(teststat5, "keyList"), dirs = "testStepR"), teststat5) expect_identical(R.cache::loadCache(attr(teststat6b, "keyList"), dirs = "testStepR"), teststat6b) unlink(file.path(R.cache::getCacheRootPath(), "testStepR"), recursive = TRUE) pathStepRdata <- NULL try(pathStepRdata <- find.package("stepRdata"), silent = TRUE) if (!is.null(pathStepRdata)) { teststat <- monteCarloSimulation(63L, intervalSystem = "dyaLen") expect_equal(computeBounds(testy, alpha = 0.1, r = 100L, intervalSystem = "dyaLen", options = list(simulation = "vector", save = list(), load = list(package = TRUE), envir = testStepR, dirs = "testStepR")), computeBounds(testy, alpha = 0.1, stat = teststat, intervalSystem = "dyaLen", options = list())) } expect_error(computeBounds(testy, alpha = 0.1, test = 1, options = list(load = list()))) expect_error(computeBounds(testy, alpha = 0.1, sd = "s", options = list(load = list()))) expect_error(computeBounds(testy, alpha = 0.1, sd = 0, options = list(load = list()))) expect_error(computeBounds(testy, alpha = 0.1, sd = c(1, 2), options = list(load = list()))) expect_error(supressWarning(computeBounds(testy, alpha = 0.1, r = 100L, seed = "s", options = list(load = list())))) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, seed = c(1, 2), options = list(load = list())), computeBounds(testy, alpha = 0.1, r = 100L, seed = 1, options = list(load = list()))) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, seed = 100.5, options = list(load = list())), computeBounds(testy, alpha = 0.1, r = 100L, seed = 100L, options = list(load = list()))) teststat <- monteCarloSimulation(n = 63L, r = 100L) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, seed = 63L, options = list(load = list())), computeBounds(testy, alpha = 0.1, r = 100L, stat = teststat)) teststat <- monteCarloSimulation(n = 36L, r = 100L) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, seed = 36L, options = list(load = list(), simulation = "matrix")), computeBounds(testy, alpha = 0.1, r = 100L, stat = teststat)) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, rand.gen = 10, options = list(load = list()))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, rand.gen = function(data, n) {rnorm(10)}, options = list(load = list()))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, rand.gen = function(data) {rnorm(10)}, options = list(load = list()))) teststat <- monteCarloSimulation(n = 63L, r = 100L) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, rand.gen = function(data) {rnorm(63)}, options = list(load = list())), computeBounds(testy, alpha = 0.1, r = 100L, stat = teststat)) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, messages = "s", options = list(load = list()))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, messages = c(10, 20), options = list(load = list()))) expect_error(computeBounds(testy, alpha = 0.1, r = 100L, messages = 0, options = list(load = list()))) expect_identical(suppressMessages(computeBounds(testy, alpha = 0.1, r = 100L, messages = 10.5, options = list(load = list()))), suppressMessages(computeBounds(testy, alpha = 0.1, r = 100L, messages = 10L, options = list(load = list())))) }) test_that("... is tested and works", { testn <- 22L testy <- rnorm(testn) testq <- rep(1, testn) expect_error(computeBounds(testy, q = testq, std = 1)) expect_error(computeBounds(testy, q = testq, intervalsystem = "all")) expect_error(computeBounds(testy, sd = "s", q = testq)) expect_error(computeBounds(testy, sd = c(1, 2), q = testq)) expect_error(computeBounds(testy, sd = NA, q = testq)) expect_error(computeBounds(c(1, 2), q = c(2, 2))) expect_error(computeBounds(testy, sd = Inf, q = testq)) expect_error(computeBounds(testy, sd = 0, q = testq)) expect_error(computeBounds(testy, sd = -0.1, q = testq)) expect_identical(computeBounds(testy, q = testq), computeBounds(testy, q = testq, sd = sdrobnorm(testy))) expect_identical(computeBounds(testy, q = testq, sd = 1L), computeBounds(testy, q = testq, sd = 1)) }) test_that("family 'hsmuce' works", { testn <- 40L testy <- rnorm(testn) testq <- rep(1, testn) expect_error(computeBounds(family = "hsmuce", q = testq)) expect_error(computeBounds(numeric(0), q = testq)) expect_identical(computeBounds(testy, family = "hsmuce", q = testq), computeBounds(testy, family = "hsmuce", intervalSystem = "dyaPar", lengths = 2^(1:5), q = testq)) expect_error(computeBounds(as.integer(testy), family = "hsmuce", q = testq)) expect_error(computeBounds(c(testy, "s"), family = "hsmuce", q = testq)) expect_error(computeBounds(c(rnorm(10), NA), family = "hsmuce", q = testq)) bounds <- computeBounds(testy, family = "hsmuce", q = testq) testIndices(bounds = bounds, indices = indicesDyaParLengths, n = testn, lengths = 2^(1:5)) testBounds(bounds = bounds, singleBounds = singleBoundsHsmuce, y = testy, criticalValues = testq) testStat(bounds = bounds, singleStat = singleStatHsmuce, y = testy, criticalValues = testq) testn <- 23L testy <- c(rnorm(10, 1, 0.23), rnorm(testn - 10, -1, 0.34)) testq <- 23:1 / 10 expect_identical(computeBounds(testy, family = "hsmuce", q = testq), computeBounds(testy, family = "hsmuce", q = testq, intervalSystem = "dyaPar")) bounds <- computeBounds(testy, family = "hsmuce", q = testq, intervalSystem = "all") testIndices(bounds = bounds, indices = indicesAllLengths, n = testn, lengths = 2:testn) testBounds(bounds = bounds, singleBounds = singleBoundsHsmuce, y = testy, criticalValues = testq) testStat(bounds = bounds, singleStat = singleStatHsmuce, y = testy, criticalValues = testq) bounds <- computeBounds(testy, family = "hsmuce", q = testq, intervalSystem = "dyaLen") testIndices(bounds = bounds, indices = indicesDyaLenLengths, n = testn, lengths = 2^(1:5)) testBounds(bounds = bounds, singleBounds = singleBoundsHsmuce, y = testy, criticalValues = testq) testStat(bounds = bounds, singleStat = singleStatHsmuce, y = testy, criticalValues = testq) testn <- 37L testy <- c(rnorm(20, 1, 0.23), rnorm(testn - 20, -1, 0.34)) testq <- 2 expect_error(computeBounds(testy, family = "hsmuce", lengths = 1L, q = testq)) expect_error(computeBounds(testy, family = "hsmuce", intervalSystem = "dyaLen", lengths = 1L, q = testq)) expect_error(computeBounds(testy, family = "hsmuce", intervalSystem = "dyaPar", lengths = 1L, q = testq)) testq <- 37:1 / 10 expect_identical(computeBounds(testy, family = "hsmuce", q = testq), computeBounds(testy, family = "hsmuce", q = testq, lengths = 2^(1:5))) testq <- 9:1 bounds <- computeBounds(testy, family = "hsmuce", q = testq, intervalSystem = "all", lengths = c(2, 5:10, 35:36)) testIndices(bounds = bounds, indices = indicesAllLengths, n = testn, lengths = c(2, 5:10, 35:36)) testBounds(bounds = bounds, singleBounds = singleBoundsHsmuce, y = testy, criticalValues = testq, lengths = c(2, 5:10, 35:36)) testStat(bounds = bounds, singleStat = singleStatHsmuce, y = testy, criticalValues = testq, lengths = c(2, 5:10, 35:36)) testq <- 3:1 / 5 bounds <- computeBounds(testy, family = "hsmuce", q = testq, intervalSystem = "dyaLen", lengths = c(2, 4, 32)) testIndices(bounds = bounds, indices = indicesDyaLenLengths, n = testn, lengths = c(2, 4, 32)) testBounds(bounds = bounds, singleBounds = singleBoundsHsmuce, y = testy, criticalValues = testq, lengths = c(2, 4, 32)) testStat(bounds = bounds, singleStat = singleStatHsmuce, y = testy, criticalValues = testq, lengths = c(2, 4, 32)) testq <- 2:1 / 5 bounds <- computeBounds(testy, family = "hsmuce", q = testq, lengths = c(2, 4)) testIndices(bounds = bounds, indices = indicesDyaParLengths, n = testn, lengths = c(2, 4)) testBounds(bounds = bounds, singleBounds = singleBoundsHsmuce, y = testy, criticalValues = testq, lengths = c(2, 4)) testStat(bounds = bounds, singleStat = singleStatHsmuce, y = testy, criticalValues = testq, lengths = c(2, 4)) testq <- 37:1 / 10 expect_error(computeBounds(testy, q = testq, family = "hsmuce", sd = 1)) expect_error(computeBounds(testy, q = testq, family = "hsmuce", intervalsystem = "all")) }) test_that("argument q is tested and works for family 'hsmuce'", { testn <- 36L testy <- c(rnorm(12, 1, 0.13), rnorm(12, -1, 0.23), rnorm(12, 1, 0.43)) teststat <- monteCarloSimulation(36L, family = "hsmuce", r = 100L) expect_warning(ret <- computeBounds(testy, family = "hsmuce")) expect_identical(ret, computeBounds(testy, family = "hsmuce", alpha = 0.5)) expect_error(computeBounds(testy, q = Inf, alpha = 0.1, stat = teststat, family = "hsmuce")) expect_error(computeBounds(testy, q = rep(1, 6), alpha = 0.1, stat = teststat, family = "hsmuce")) expect_error(computeBounds(testy, q = rep(1, 4), alpha = 0.1, stat = teststat, family = "hsmuce")) testq <- 1:5 attr(testq, "n") <- "s" expect_error(computeBounds(testy, q = testq, alpha = 0.1, stat = teststat, family = "hsmuce")) attr(testq, "n") <- 35L expect_error(computeBounds(testy, q = testq, alpha = 0.1, stat = teststat, family = "hsmuce")) expect_identical(computeBounds(testy, q = 3, family = "hsmuce", intervalSystem = "all", lengths = c(2:3, 8:23), penalty = "sqrt"), computeBounds(testy, family = "hsmuce", intervalSystem = "all", lengths = c(2:3, 8:23), q = critVal(q = 3, family = "hsmuce", intervalSystem = "all", lengths = c(2:3, 8:23), n = testn, penalty = "sqrt"))) expect_identical(computeBounds(testy, q = 3, intervalSystem = "dyaLen", lengths = c(2, 4, 8, 32), nq = 45L, penalty = "none"), computeBounds(testy, intervalSystem = "dyaLen", lengths = c(2, 4, 8, 32), q = critVal(q = 3, intervalSystem = "dyaLen", lengths = c(2, 4, 8, 32), n = testn, nq = 45L, penalty = "none"))) expect_identical(computeBounds(testy, q = 3, intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32), penalty = "log"), computeBounds(testy, intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32), q = critVal(q = 3, intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32), n = testn, penalty = "log"))) testq <- 1:45 attr(testq, "n") <- 45L expect_identical(computeBounds(testy, family = "hsmuce", intervalSystem = "all", q = testq), computeBounds(testy, family = "hsmuce", intervalSystem = "all", q = 2:36)) testq <- 2:45 attr(testq, "n") <- 45L expect_identical(computeBounds(testy, family = "hsmuce", intervalSystem = "all", q = testq), computeBounds(testy, family = "hsmuce", intervalSystem = "all", q = 2:36)) testq <- 1:36 attr(testq, "n") <- 45L expect_identical(computeBounds(testy, family = "hsmuce", intervalSystem = "all", q = testq), computeBounds(testy, family = "hsmuce", intervalSystem = "all", q = 2:36)) expect_identical(computeBounds(testy, family = "hsmuce", intervalSystem = "all", q = 1:36, lengths = 3:23), computeBounds(testy, family = "hsmuce", intervalSystem = "all", q = 3:23, lengths = 3:23)) expect_identical(computeBounds(testy, q = 1:36, family = "hsmuce", intervalSystem = "dyaLen"), computeBounds(testy, q = 2^(1:5), family = "hsmuce", intervalSystem = "dyaLen")) testq <- 2^(1:6) attr(testq, "n") <- 64L expect_identical(computeBounds(testy, q = testq, family = "hsmuce", intervalSystem = "dyaPar"), computeBounds(testy, q = 2^(1:5), family = "hsmuce", intervalSystem = "dyaPar")) ret <- computeBounds(testy, family = "hsmuce", alpha = 0.1, stat = teststat) expect_identical(ret, computeBounds(testy, family = "hsmuce", alpha = 0.1, stat = teststat, nq = testn, intervalSystem = "dyaPar", lengths = 2^(1:5), penalty = "weights", weights = rep(0.2, 5))) expect_identical(ret, computeBounds(testy, family = "hsmuce", q = critVal(family = "hsmuce", alpha = 0.1, stat = teststat, n = testn))) expect_error(computeBounds(testy, family = "hsmuce", alpha = "s", stat = teststat)) expect_identical(computeBounds(testy, family = "hsmuce", alpha = 0.075, stat = teststat), computeBounds(testy, family = "hsmuce", q = critVal(alpha = 0.075, family = "hsmuce", stat = teststat, n = testn))) expect_error(computeBounds(testy, family = "hsmuce", alpha = 0.1, stat = teststat, n = testn)) expect_error(computeBounds(testy, alpha = 0.1, family = "hsmuce", weights = NA, stat = teststat)) teststat <- monteCarloSimulation(n = 36L, r = 100L, family = "hsmuce", intervalSystem = "all") expect_identical(computeBounds(testy, family = "hsmuce", alpha = 0.14, penalty = "log", stat = teststat, intervalSystem = "all", lengths = c(2, 5, 8, 23)), computeBounds(testy, family = "hsmuce", intervalSystem = "all", lengths = c(2, 5, 8, 23), q = critVal(alpha = 0.14, family = "hsmuce", intervalSystem = "all", lengths = c(2, 5, 8, 23), penalty = "log", stat = teststat, n = testn))) teststat <- monteCarloSimulation(n = 36L, r = 100L, family = "hsmuce", intervalSystem = "dyaLen") expect_identical(computeBounds(testy, family = "hsmuce", alpha = 0.034, penalty = "none", stat = teststat, intervalSystem = "dyaLen", lengths = c(2, 4, 8, 32)), computeBounds(testy, family = "hsmuce", intervalSystem = "dyaLen", lengths = c(2, 4, 8, 32), q = critVal(alpha = 0.034, family = "hsmuce", intervalSystem = "dyaLen", lengths = c(2, 4, 8, 32), penalty = "none", stat = teststat, n = testn))) teststat <- monteCarloSimulation(n = 36L, r = 100L, family = "hsmuce") expect_identical(computeBounds(testy, family = "hsmuce", alpha = 0.56, penalty = "weights", weights = c(0.2, 0.3, 0.4, 0.1), stat = teststat, intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32)), computeBounds(testy, family = "hsmuce", intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32), q = critVal(alpha = 0.56, family = "hsmuce", intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32), penalty = "weights", weights = c(0.2, 0.3, 0.4, 0.1), stat = teststat, n = testn))) expect_identical(computeBounds(testy, family = "hsmuce", alpha = 0.014, stat = teststat, nq = 100L, intervalSystem = "dyaPar", lengths = 2^c(1:3, 5)), computeBounds(testy, family = "hsmuce", intervalSystem = "dyaPar", lengths = 2^c(1:3, 5), q = critVal(alpha = 0.014, family = "hsmuce", intervalSystem = "dyaPar", lengths = 2^c(1:3, 5), stat = teststat, n = testn, nq = 100L))) expect_error(computeBounds(testy, family = "hsmuce", alpha = 0.1, output = "vector", stat = teststat)) expect_error(computeBounds(testy, family = "hsmuce", alpha = 0.1, data = 1, stat = teststat)) expect_error(computeBounds(testy, alpha = 0.1, family = "hsmuce", stat = rnorm(1e4))) teststatmatrix <- monteCarloSimulation(n = 36L, r = 100L, intervalSystem = "all", family = "hsmuce") teststatvector <- monteCarloSimulation(n = 36L, r = 100L, output = "maximum", intervalSystem = "all", penalty = "sqrt", family = "hsmuce") expect_identical(computeBounds(testy, family = "hsmuce", intervalSystem = "all", penalty = "sqrt", alpha = 0.05, stat = teststatvector), computeBounds(testy, family = "hsmuce", intervalSystem = "all", q = critVal(family = "hsmuce", intervalSystem = "all", alpha = 0.05, penalty = "sqrt", stat = teststatmatrix, n = testn))) teststatmatrix <- monteCarloSimulation(n = 36L, r = 100L, intervalSystem = "dyaPar", family = "hsmuce") teststatvector <- monteCarloSimulation(n = 36L, r = 100L, output = "maximum", intervalSystem = "dyaPar", penalty = "sqrt", family = "hsmuce", lengths = c(2, 8, 16, 32)) expect_identical(computeBounds(testy, alpha = 0.122, stat = teststatvector, nq = 2^9L, family = "hsmuce", intervalSystem = "dyaPar", lengths = c(2, 8, 16, 32), penalty = "sqrt"), computeBounds(testy, family = "hsmuce", intervalSystem = "dyaPar", lengths = c(2, 8, 16, 32), q = critVal(alpha = 0.122, stat = teststatmatrix, n = testn, nq = 2^9L, family = "hsmuce", intervalSystem = "dyaPar", lengths = c(2, 8, 16, 32), penalty = "sqrt"))) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, intervalSystem = "dyaPar", lengths = c(2, 4, 8), penalty = "log", family = "hsmuce", options = list(simulation = "vector", save = list(), load = list())), computeBounds(testy, intervalSystem = "dyaPar", family = "hsmuce", lengths = c(2, 4, 8), q = critVal(n = length(testy), alpha = 0.1, r = 100L, intervalSystem = "dyaPar", lengths = c(2, 4, 8), penalty = "log", family = "hsmuce", options = list(simulation = "vector", save = list(), load = list())))) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, family = "hsmuce", weights = c(0.4, 0.2, 0.1, 0.1, 0.2), options = list(simulation = "matrixIncreased", save = list(), load = list())), computeBounds(testy, family = "hsmuce", q = critVal(n = length(testy), alpha = 0.1, r = 100L, family = "hsmuce" , weights = c(0.4, 0.2, 0.1, 0.1, 0.2), options = list(simulation = "matrixIncreased", save = list(), load = list())))) }) test_that("family 'mDependentPS' works", { testn <- 20L testy <- rnorm(testn) testq <- rep(1, testn) testcovariances <- as.numeric(ARMAacf(ar = c(), ma = c(0.8, 0.5, 0.3), lag.max = 3)) expect_error(computeBounds(family = "mDependentPS", q = testq, covariances = testcovariances)) expect_error(computeBounds(numeric(0), q = testq, covariances = testcovariances)) expect_identical(computeBounds(testy, family = "mDependentPS", q = testq, covariances = testcovariances), computeBounds(testy, family = "mDependentPS", intervalSystem = "dyaLen", lengths = 2^(0:4), q = testq, covariances = testcovariances)) expect_error(computeBounds(as.integer(testy), family = "mDependentPS", q = testq, covariances = testcovariances)) expect_error(computeBounds(c(testy, "s"), family = "mDependentPS", q = testq, covariances = testcovariances)) expect_error(computeBounds(c(rnorm(10), NA), family = "mDependentPS", q = testq, covariances = testcovariances)) bounds <- computeBounds(testy, family = "mDependentPS", q = testq, covariances = testcovariances) testIndices(bounds = bounds, indices = indicesDyaLen, n = testn, lengths = 2^(0:4)) testBounds(bounds = bounds, singleBounds = singleBoundsmDependentPS, y = testy, criticalValues = testq, covariances = testcovariances) testStat(bounds = bounds, singleStat = singleStatmDependentPS, y = testy, criticalValues = testq, covariances = testcovariances) testn <- 23L testy <- c(rnorm(10, 1, 0.23), rnorm(testn - 10, -1, 0.34)) testq <- 23:1 / 10 testcovariances <- as.numeric(ARMAacf(ar = c(), ma = c(0.6, 0.5), lag.max = 2)) expect_identical(computeBounds(testy, family = "mDependentPS", q = testq, covariances = testcovariances), computeBounds(testy, family = "mDependentPS", q = testq, intervalSystem = "dyaLen", covariances = testcovariances)) bounds <- computeBounds(testy, family = "mDependentPS", q = testq, intervalSystem = "all", covariances = testcovariances) testIndices(bounds = bounds, indices = indicesAll, n = testn, lengths = 1:testn) testBounds(bounds = bounds, singleBounds = singleBoundsmDependentPS, y = testy, criticalValues = testq, covariances = testcovariances) testStat(bounds = bounds, singleStat = singleStatmDependentPS, y = testy, criticalValues = testq, covariances = testcovariances) bounds <- computeBounds(testy, family = "mDependentPS", q = testq, intervalSystem = "dyaPar", covariances = testcovariances) testIndices(bounds = bounds, indices = indicesDyaPar, n = testn, lengths = 2^(0:4)) testBounds(bounds = bounds, singleBounds = singleBoundsmDependentPS, y = testy, criticalValues = testq, covariances = testcovariances) testStat(bounds = bounds, singleStat = singleStatmDependentPS, y = testy, criticalValues = testq, covariances = testcovariances) testn <- 37L testy <- c(rnorm(20, 1, 0.23), rnorm(testn - 20, -1, 0.34)) testcovariances <- as.numeric(ARMAacf(ar = c(), ma = c(0.8, 0.5, 0.3, 0.1, 0.05), lag.max = 5)) testq <- 37:1 / 10 expect_identical(computeBounds(testy, family = "mDependentPS", q = testq, covariances = testcovariances), computeBounds(testy, family = "mDependentPS", q = testq, lengths = 2^(0:5), covariances = testcovariances)) testq <- 9:1 bounds <- computeBounds(testy, family = "mDependentPS", q = testq, intervalSystem = "all", lengths = c(2, 5:10, 35:36), covariances = testcovariances) testIndices(bounds = bounds, indices = indicesAllLengths, n = testn, lengths = c(2, 5:10, 35:36)) testBounds(bounds = bounds, singleBounds = singleBoundsmDependentPS, y = testy, criticalValues = testq, lengths = c(2, 5:10, 35:36), covariances = testcovariances) testStat(bounds = bounds, singleStat = singleStatmDependentPS, y = testy, criticalValues = testq, lengths = c(2, 5:10, 35:36), covariances = testcovariances) testq <- 3:1 / 5 bounds <- computeBounds(testy, family = "mDependentPS", q = testq, lengths = c(1, 4, 32), covariances = testcovariances) testIndices(bounds = bounds, indices = indicesDyaLenLengths, n = testn, lengths = c(1, 4, 32)) testBounds(bounds = bounds, singleBounds = singleBoundsmDependentPS, y = testy, criticalValues = testq, lengths = c(1, 4, 32), covariances = testcovariances) testStat(bounds = bounds, singleStat = singleStatmDependentPS, y = testy, criticalValues = testq, lengths = c(1, 4, 32), covariances = testcovariances) testq <- 2:1 / 5 bounds <- computeBounds(testy, family = "mDependentPS", q = testq, intervalSystem = "dyaPar", lengths = c(2, 4), covariances = testcovariances) testIndices(bounds = bounds, indices = indicesDyaParLengths, n = testn, lengths = c(2, 4)) testBounds(bounds = bounds, singleBounds = singleBoundsmDependentPS, y = testy, criticalValues = testq, lengths = c(2, 4), covariances = testcovariances) testStat(bounds = bounds, singleStat = singleStatmDependentPS, y = testy, criticalValues = testq, lengths = c(2, 4), covariances = testcovariances) }) test_that("argument q is tested and works for family 'mDependentPS'", { testn <- 36L testy <- c(rnorm(12, 10, 0.13), rnorm(12, -10, 0.13), rnorm(12, 10, 0.13)) testcovariances <- as.numeric(ARMAacf(ar = c(), ma = c(0.8, 0.5, 0.3), lag.max = 3)) teststat <- monteCarloSimulation(n = 36L, r = 100L, family = "mDependentPS", covariances = testcovariances) expect_warning(ret <- computeBounds(testy, family = "mDependentPS", covariances = testcovariances)) expect_identical(ret, computeBounds(testy, family = "mDependentPS", covariances = testcovariances, alpha = 0.5)) expect_error(computeBounds(testy, q = rep(1, 7), alpha = 0.1, stat = teststat, family = "mDependentPS", covariances = testcovariances)) expect_error(computeBounds(testy, q = rep(1, 4), alpha = 0.1, stat = teststat, family = "mDependentPS", covariances = testcovariances)) expect_identical(computeBounds(testy, q = 3, family = "mDependentPS", intervalSystem = "all", lengths = c(2:3, 8:23), penalty = "sqrt", covariances = testcovariances), computeBounds(testy, family = "mDependentPS", intervalSystem = "all", lengths = c(2:3, 8:23), covariances = testcovariances, q = critVal(q = 3, family = "mDependentPS", intervalSystem = "all", lengths = c(2:3, 8:23), n = testn, penalty = "sqrt", covariances = testcovariances))) expect_identical(computeBounds(testy, q = 3, family = "mDependentPS", intervalSystem = "dyaLen", lengths = c(2, 4, 8, 32), nq = 45L, penalty = "none", covariances = testcovariances), computeBounds(testy, family = "mDependentPS", intervalSystem = "dyaLen", lengths = c(2, 4, 8, 32), covariances = testcovariances, q = critVal(q = 3, family = "mDependentPS", intervalSystem = "dyaLen", lengths = c(2, 4, 8, 32), n = testn, nq = 45L, penalty = "none", covariances = testcovariances))) expect_identical(computeBounds(testy, q = 3, family = "mDependentPS", intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32), penalty = "log", covariances = testcovariances), computeBounds(testy, family = "mDependentPS", intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32), covariances = testcovariances, q = critVal(q = 3, family = "mDependentPS", intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32), n = testn, penalty = "log", covariances = testcovariances))) testq <- 1:45 attr(testq, "n") <- 45L expect_identical(computeBounds(testy, family = "mDependentPS", intervalSystem = "all", q = testq, covariances = testcovariances), computeBounds(testy, family = "mDependentPS", intervalSystem = "all", q = 1:36, covariances = testcovariances)) expect_identical(computeBounds(testy, family = "mDependentPS", intervalSystem = "all", q = 1:36, lengths = 3:23, covariances = testcovariances), computeBounds(testy, family = "mDependentPS", intervalSystem = "all", q = 3:23, lengths = 3:23, covariances = testcovariances)) expect_identical(computeBounds(testy, q = 1:36, family = "mDependentPS", intervalSystem = "dyaLen", covariances = testcovariances), computeBounds(testy, q = 2^(0:5), family = "mDependentPS", intervalSystem = "dyaLen", covariances = testcovariances)) testq <- 2^(0:6) attr(testq, "n") <- 64L expect_identical(computeBounds(testy, q = testq, family = "mDependentPS", intervalSystem = "dyaPar", covariances = testcovariances), computeBounds(testy, q = 2^(0:5), family = "mDependentPS", intervalSystem = "dyaPar", covariances = testcovariances)) ret <- computeBounds(testy, family = "mDependentPS", alpha = 0.1, stat = teststat, covariances = testcovariances) expect_identical(ret, computeBounds(testy, family = "mDependentPS", alpha = 0.1, stat = teststat, nq = testn, intervalSystem = "dyaLen", lengths = 2^(0:5), penalty = "sqrt", covariances = testcovariances)) expect_identical(ret, computeBounds(testy, family = "mDependentPS", covariances = testcovariances, q = critVal(family = "mDependentPS", alpha = 0.1, stat = teststat, n = testn, covariances = testcovariances))) expect_error(computeBounds(testy, family = "mDependentPS", alpha = "s", stat = teststat, covariances = testcovariances)) expect_identical(computeBounds(testy, family = "mDependentPS", alpha = 0.075, stat = teststat, covariances = testcovariances), computeBounds(testy, family = "mDependentPS", covariances = testcovariances, q = critVal(alpha = 0.075, family = "mDependentPS", stat = teststat, n = testn, covariances = testcovariances))) expect_error(computeBounds(testy, family = "mDependentPS", alpha = 0.1, stat = teststat, n = testn, covariances = testcovariances)) expect_error(computeBounds(testy, alpha = 0.1, family = "mDependentPS", penalty = "weights", weights = NA, stat = teststat, covariances = testcovariances)) teststat <- monteCarloSimulation(n = 36L, r = 100L, family = "mDependentPS", covariances = testcovariances, intervalSystem = "all") expect_identical(computeBounds(testy, family = "mDependentPS", alpha = 0.14, penalty = "log", stat = teststat, intervalSystem = "all", lengths = c(2, 5, 8, 23), covariances = testcovariances), computeBounds(testy, family = "mDependentPS", intervalSystem = "all", lengths = c(2, 5, 8, 23), covariances = testcovariances, q = critVal(alpha = 0.14, family = "mDependentPS", intervalSystem = "all", lengths = c(2, 5, 8, 23), penalty = "log", stat = teststat, n = testn, covariances = testcovariances))) teststat <- monteCarloSimulation(n = 36L, r = 100L, family = "mDependentPS", covariances = testcovariances, intervalSystem = "dyaLen") expect_identical(computeBounds(testy, family = "mDependentPS", alpha = 0.034, penalty = "none", stat = teststat, intervalSystem = "dyaLen", lengths = c(2, 4, 8, 32), covariances = testcovariances), computeBounds(testy, family = "mDependentPS", intervalSystem = "dyaLen", lengths = c(2, 4, 8, 32), covariances = testcovariances, q = critVal(alpha = 0.034, family = "mDependentPS", intervalSystem = "dyaLen", lengths = c(2, 4, 8, 32), penalty = "none", stat = teststat, n = testn, covariances = testcovariances))) teststat <- monteCarloSimulation(n = 36L, r = 100L, family = "mDependentPS", covariances = testcovariances, intervalSystem = "dyaPar") expect_identical(computeBounds(testy, family = "mDependentPS", alpha = 0.56, penalty = "weights", weights = c(0.2, 0.3, 0.4, 0.1), stat = teststat, intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32), covariances = testcovariances), computeBounds(testy, family = "mDependentPS", intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32), covariances = testcovariances, q = critVal(alpha = 0.56, family = "mDependentPS", intervalSystem = "dyaPar", lengths = c(2, 4, 8, 32), penalty = "weights", weights = c(0.2, 0.3, 0.4, 0.1), stat = teststat, n = testn, covariances = testcovariances))) expect_identical(computeBounds(testy, family = "mDependentPS", alpha = 0.014, stat = teststat, nq = 100L, intervalSystem = "dyaPar", lengths = 2^c(0:3, 5), covariances = testcovariances), computeBounds(testy, family = "mDependentPS", intervalSystem = "dyaPar", lengths = 2^c(0:3, 5), covariances = testcovariances, q = critVal(alpha = 0.014, family = "mDependentPS", intervalSystem = "dyaPar", lengths = 2^c(0:3, 5), stat = teststat, n = testn, nq = 100L, covariances = testcovariances))) expect_error(computeBounds(testy, family = "mDependentPS", alpha = 0.1, output = "vector", stat = teststat, covariances = testcovariances)) expect_error(computeBounds(testy, family = "mDependentPS", alpha = 0.1, data = 1, stat = teststat, covariances = testcovariances)) expect_error(computeBounds(testy, family = "mDependentPS", covariances = testcovariances, alpha = 0.1, output = "vector", stat = teststat)) expect_error(computeBounds(testy, family = "mDependentPS", covariances = testcovariances, alpha = 0.1, data = 1, stat = teststat)) expect_error(computeBounds(testy, alpha = 0.1, family = "mDependentPS", covariances = testcovariances, stat = rnorm(1e4), penalty = "weights")) teststatmatrix <- monteCarloSimulation(n = 36L, r = 100L, family = "mDependentPS", covariances = testcovariances, intervalSystem = "all") teststatvector <- monteCarloSimulation(n = 36L, r = 100L, family = "mDependentPS", covariances = testcovariances, output = "maximum", intervalSystem = "all") expect_identical(computeBounds(testy, family = "mDependentPS", covariances = testcovariances, intervalSystem = "all", penalty = "sqrt", alpha = 0.078, stat = teststatvector), computeBounds(testy, family = "mDependentPS", covariances = testcovariances, intervalSystem = "all", q = critVal(family = "mDependentPS", covariances = testcovariances, intervalSystem = "all", alpha = 0.078, penalty = "sqrt", stat = teststatmatrix, n = testn))) teststatmatrix <- monteCarloSimulation(n = 36L, r = 100L, family = "mDependentPS", covariances = testcovariances) teststatvector <- monteCarloSimulation(n = 36L, r = 100L, family = "mDependentPS", covariances = testcovariances, output = "maximum", lengths = c(2, 8, 16, 32)) expect_identical(computeBounds(testy, alpha = 0.122, stat = teststatvector, nq = 2^9L, family = "mDependentPS", covariances = testcovariances, lengths = c(2, 8, 16, 32)), computeBounds(testy, family = "mDependentPS", covariances = testcovariances, lengths = c(2, 8, 16, 32), q = critVal(alpha = 0.122, stat = teststatmatrix, n = testn, nq = 2^9L, family = "mDependentPS", covariances = testcovariances, lengths = c(2, 8, 16, 32)))) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, lengths = 3:17, penalty = "log", nq = 100, family = "mDependentPS", covariances = testcovariances, intervalSystem = "all", options = list(simulation = "vectorIncreased", save = list(), load = list())), computeBounds(testy, lengths = 3:17, family = "mDependentPS", covariances = testcovariances, intervalSystem = "all", q = critVal(n = 100, alpha = 0.1, r = 100L, lengths = 3:17, intervalSystem = "all", penalty = "log", family = "mDependentPS", covariances = testcovariances, options = list(simulation = "vector", save = list(), load = list())))) testStepR <- new.env() teststat <- monteCarloSimulation(36L, r = 100L, family = "mDependentPS", covariances = testcovariances) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, family = "mDependentPS", covariances = testcovariances, options = list(simulation = "matrix", save = list(workspace = "matrix"), load = list(), envir = testStepR)), computeBounds(testy, alpha = 0.1, stat = teststat, family = "mDependentPS", covariances = testcovariances, options = list())) expect_identical(get("critValStepRTab", envir = testStepR, inherits = FALSE)$stat[[1]], teststat) expect_identical(length(get("critValStepRTab", envir = testStepR, inherits = FALSE)$stat), 1L) expect_identical(critVal(36L, alpha = 0.1, r = 50L, output = "vector", family = "mDependentPS", covariances = testcovariances + 1e-12, options = list(simulation = "matrix", save = list(), load = list(workspace = "matrix"), envir = testStepR)), critVal(36L, alpha = 0.1, stat = teststat, output = "vector", options = list(), family = "mDependentPS", covariances = testcovariances)) remove(critValStepRTab, envir = testStepR) }) test_that("arguments in ... are tested and work for family mDependentPS", { testn <- 17L testcovariances <- as.numeric(ARMAacf(ar = c(), ma = c(0.8, 0.5, 0.3), lag.max = 3)) testcorrelations <- testcovariances / testcovariances[1] testsignal <- list(leftIndex = c(1L, 13L), rightIndex = c(12L, testn), value = c(0, -1)) testfilter <- list(acf = testcorrelations) class(testfilter) <- c("lowpassFilter", class(testfilter)) testy <- as.numeric(arima.sim(n = testn, list(ar = c(), ma = c(0.8, 0.5, 0.3)), sd = 1)) testq = 17:1 / 3 expect_error(computeBounds(testy, family = "mDependentPS", q = testq, covariances = testcovariances, std = 1)) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, correlations = testcorrelations, std = 1)) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, filter = testfilter, std = 1)) expect_error(computeBounds(testy, family = "mDependentPS", intervalsystem = "all")) expect_error(computeBounds(testy, family = "mDependentPS", q = testq)) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, sd = 1)) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, covariances = c(testcovariances, "s"))) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, covariances = c(testcovariances, NA))) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, covariances = c(testcovariances, Inf))) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, covariances = c(0.01, testcovariances))) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, covariances = c(-1, testcovariances))) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, correlations = c(testcorrelations, "s"))) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, correlations = c(testcorrelations, NA))) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, correlations = c(testcorrelations, Inf))) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, correlations = c(testcorrelations, 1.1))) expect_error(ccomputeBounds(testy, family = "mDependentPS", q = testq, correlations = c(0.99, testcorrelations[-1]))) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, sd = "s", correlations = testcorrelations)) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, sd = c(1, 2), correlations = testcorrelations)) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, sd = NA, correlations = testcorrelations)) expect_error(computeBounds(c(1, 2), q = c(5, 4), family = "mDependentPS", correlations = testcorrelations)) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, sd = Inf, correlations = testcorrelations)) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, sd = 0, correlations = testcorrelations)) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, sd = -0.1, correlations = testcorrelations)) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, filter = list(param = list(acf = testcorrelations)))) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, sd = "s", filter = testfilter)) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, sd = c(1, 2), filter = testfilter)) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, sd = NA, filter = testfilter)) expect_error(computeBounds(c(1, 2), q = c(5, 4), family = "mDependentPS", filter = testfilter)) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, sd = Inf, filter = testfilter)) expect_error(computeBounds(testy, family = "mDependentPS", q = testq, sd = 0, filter = testfilter)) expect_error(ccomputeBounds(testy, family = "mDependentPS", q = testq, sd = -0.1, filter = testfilter)) expect_identical(computeBounds(testy, family = "mDependentPS", q = testq, covariances = sdrobnorm(testy, lag = 4)^2 * testcorrelations), computeBounds(testy, family = "mDependentPS", q = testq, correlations = testcorrelations)) expect_identical(computeBounds(testy, family = "mDependentPS", q = testq, covariances = 1.1^2 * testcorrelations), computeBounds(testy, family = "mDependentPS", q = testq, correlations = testcorrelations, sd = 1.1)) expect_identical(computeBounds(testy, family = "mDependentPS", q = testq, covariances = sdrobnorm(testy, lag = 4)^2 * testcorrelations), computeBounds(testy, family = "mDependentPS", q = testq, filter = testfilter)) expect_identical(computeBounds(testy, family = "mDependentPS", q = testq, covariances = 1.1^2 * testcorrelations), computeBounds(testy, family = "mDependentPS", q = testq, filter = testfilter, sd = 1.1)) }) test_that("family 'jsmurf' works", { testn <- 70L testy <- rnorm(testn) testq <- rep(1, testn) testfilter <- lowpassFilter::lowpassFilter(type = "bessel", param = list(pole = 4L, cutoff = 0.1), sr = 1e4) expect_error(computeBounds(family = "jsmurf", q = testq, filter = testfilter)) expect_error(computeBounds(numeric(0), q = testq, filter = testfilter)) expect_identical(computeBounds(testy, family = "jsmurf", q = testq, filter = testfilter), computeBounds(testy, family = "jsmurf", intervalSystem = "dyaLen", lengths = 2^(4:6), q = testq, filter = testfilter)) expect_error(computeBounds(as.integer(testy), family = "jsmurf", q = testq, filter = testfilter)) expect_error(computeBounds(c(testy, "s"), family = "jsmurf", q = testq, filter = testfilter)) expect_error(computeBounds(c(rnorm(10), NA), family = "jsmurf", q = testq, filter = testfilter)) bounds <- computeBounds(testy, family = "jsmurf", q = testq, filter = testfilter, sd = 1) testIndices(bounds = bounds, indices = indicesDyaLenLengths, n = testn, lengths = 2^(4:6)) testBounds(bounds = bounds, singleBounds = singleBoundsJsmurf, y = testy, criticalValues = testq, filter = testfilter, sd = 1) testStat(bounds = bounds, singleStat = singleStatJsmurf, y = testy, criticalValues = testq, filter = testfilter, sd = 1) bounds <- computeBounds(testy, family = "jsmurfPS", q = testq, filter = testfilter, sd = 1) testIndices(bounds = bounds, indices = indicesDyaLenLengths, n = testn, lengths = 2^(4:6)) testBounds(bounds = bounds, singleBounds = singleBoundsJsmurfPS, y = testy, criticalValues = testq, filter = testfilter, sd = 1) testStat(bounds = bounds, singleStat = singleStatJsmurfPS, y = testy, criticalValues = testq, filter = testfilter, sd = 1) bounds <- computeBounds(testy, family = "jsmurfLR", q = testq, filter = testfilter, sd = 1) testIndices(bounds = bounds, indices = indicesDyaLenLengths, n = testn, lengths = 2^(4:6)) testBounds(bounds = bounds, singleBounds = singleBoundsJsmurfLR, y = testy, criticalValues = testq, filter = testfilter, sd = 1) testStat(bounds = bounds, singleStat = singleStatJsmurfLR, y = testy, criticalValues = testq, filter = testfilter, sd = 1) testn <- 23L testy <- c(rnorm(10, 1, 0.23), rnorm(testn - 10, -1, 0.34)) testq <- 23:1 / 10 testfilter <- lowpassFilter::lowpassFilter(type = "bessel", param = list(pole = 6L, cutoff = 0.2), sr = 1e4) expect_identical(computeBounds(testy, family = "jsmurf", q = testq, filter = testfilter), computeBounds(testy, family = "jsmurf", q = testq, intervalSystem = "dyaLen", filter = testfilter)) expect_identical(computeBounds(testy, family = "jsmurfPS", q = testq, filter = testfilter), computeBounds(testy, family = "jsmurfPS", q = testq, intervalSystem = "dyaLen", filter = testfilter)) expect_identical(computeBounds(testy, family = "jsmurfLR", q = testq, filter = testfilter), computeBounds(testy, family = "jsmurfLR", q = testq, intervalSystem = "dyaLen", filter = testfilter)) bounds <- computeBounds(testy, family = "jsmurf", q = testq, intervalSystem = "all", filter = testfilter, sd = 1) testIndices(bounds = bounds, indices = indicesAllLengths, n = testn, lengths = (testfilter$len + 1):testn) testBounds(bounds = bounds, singleBounds = singleBoundsJsmurf, y = testy, criticalValues = testq, filter = testfilter, sd = 1) testStat(bounds = bounds, singleStat = singleStatJsmurf, y = testy, criticalValues = testq, filter = testfilter, sd = 1) bounds <- computeBounds(testy, family = "jsmurfPS", q = testq, intervalSystem = "all", filter = testfilter, sd = 1) testIndices(bounds = bounds, indices = indicesAllLengths, n = testn, lengths = (testfilter$len + 1):testn) testBounds(bounds = bounds, singleBounds = singleBoundsJsmurfPS, y = testy, criticalValues = testq, filter = testfilter, sd = 1) testStat(bounds = bounds, singleStat = singleStatJsmurfPS, y = testy, criticalValues = testq, filter = testfilter, sd = 1) bounds <- computeBounds(testy, family = "jsmurfLR", q = testq, intervalSystem = "all", filter = testfilter, sd = 1) testIndices(bounds = bounds, indices = indicesAllLengths, n = testn, lengths = (testfilter$len + 1):testn) testBounds(bounds = bounds, singleBounds = singleBoundsJsmurfLR, y = testy, criticalValues = testq, filter = testfilter, sd = 1) testStat(bounds = bounds, singleStat = singleStatJsmurfLR, y = testy, criticalValues = testq, filter = testfilter, sd = 1) testn <- 37L testy <- c(rnorm(20, 1, 0.23), rnorm(testn - 20, -1, 0.34)) testfilter <- lowpassFilter::lowpassFilter(type = "bessel", param = list(pole = 4L, cutoff = 0.0789), sr = 1e4) testq <- 37:1 / 10 expect_identical(computeBounds(testy, family = "jsmurf", q = testq, filter = testfilter), computeBounds(testy, family = "jsmurf", q = testq, lengths = 2^(4:5), filter = testfilter)) expect_identical(computeBounds(testy, family = "jsmurfPS", q = testq, filter = testfilter), computeBounds(testy, family = "jsmurfPS", q = testq, lengths = 2^(4:5), filter = testfilter)) expect_identical(computeBounds(testy, family = "jsmurfLR", q = testq, filter = testfilter), computeBounds(testy, family = "jsmurfLR", q = testq, lengths = 2^(4:5), filter = testfilter)) testq <- 6:1 bounds <- computeBounds(testy, family = "jsmurf", q = testq, intervalSystem = "all", lengths = c(16:19, 35:36), filter = testfilter, sd = 1) testIndices(bounds = bounds, indices = indicesAllLengths, n = testn, lengths = c(16:19, 35:36)) testBounds(bounds = bounds, singleBounds = singleBoundsJsmurf, y = testy, criticalValues = testq, lengths = c(16:19, 35:36), filter = testfilter, sd = 1) testStat(bounds = bounds, singleStat = singleStatJsmurf, y = testy, criticalValues = testq, lengths = c(16:19, 35:36), filter = testfilter, sd = 1) bounds <- computeBounds(testy, family = "jsmurfPS", q = testq, intervalSystem = "all", lengths = c(16:19, 35:36), filter = testfilter, sd = 1) testIndices(bounds = bounds, indices = indicesAllLengths, n = testn, lengths = c(16:19, 35:36)) testBounds(bounds = bounds, singleBounds = singleBoundsJsmurfPS, y = testy, criticalValues = testq, lengths = c(16:19, 35:36), filter = testfilter, sd = 1) testStat(bounds = bounds, singleStat = singleStatJsmurfPS, y = testy, criticalValues = testq, lengths = c(16:19, 35:36), filter = testfilter, sd = 1) }) test_that("argument q is tested and works for family 'jsmurf'", { testn <- 36L testy <- c(rnorm(12, 10, 0.13), rnorm(12, -10, 0.13), rnorm(12, 10, 0.13)) testfilter <- lowpassFilter::lowpassFilter(type = "bessel", param = list(pole = 4L, cutoff = 0.1), sr = 1e4) teststat <- monteCarloSimulation(n = 36L, r = 100L, family = "jsmurf", filter = testfilter) expect_warning(ret <- computeBounds(testy, family = "jsmurf", filter = testfilter)) expect_identical(ret, computeBounds(testy, family = "jsmurf", filter = testfilter, alpha = 0.5)) expect_error(computeBounds(testy, q = rep(1, 7), alpha = 0.1, stat = teststat, family = "jsmurf", filter = testfilter)) expect_error(computeBounds(testy, q = rep(1, 4), alpha = 0.1, stat = teststat, family = "jsmurf", filter = testfilter)) expect_identical(computeBounds(testy, q = 3, family = "jsmurf", intervalSystem = "all", lengths = c(13:23, 25:27), penalty = "sqrt", filter = testfilter), computeBounds(testy, family = "jsmurf", intervalSystem = "all", lengths = c(13:23, 25:27), filter = testfilter, q = critVal(q = 3, family = "jsmurf", intervalSystem = "all", lengths = c(13:23, 25:27), n = testn, penalty = "sqrt", filter = testfilter))) testq <- 1:45 attr(testq, "n") <- 45L expect_identical(computeBounds(testy, family = "jsmurf", intervalSystem = "all", q = testq, filter = testfilter), computeBounds(testy, family = "jsmurf", intervalSystem = "all", q = 1:36, filter = testfilter)) expect_identical(computeBounds(testy, family = "jsmurf", intervalSystem = "all", q = 1:36, lengths = 13:23, filter = testfilter), computeBounds(testy, family = "jsmurf", intervalSystem = "all", q = 13:23, lengths = 13:23, filter = testfilter)) ret <- computeBounds(testy, family = "jsmurf", alpha = 0.1, stat = teststat, filter = testfilter) expect_identical(ret, computeBounds(testy, family = "jsmurf", alpha = 0.1, stat = teststat, nq = testn, intervalSystem = "dyaLen", lengths = 2^(4:5), penalty = "sqrt", filter = testfilter)) expect_identical(ret, computeBounds(testy, family = "jsmurf", filter = testfilter, q = critVal(family = "jsmurf", alpha = 0.1, stat = teststat, n = testn, filter = testfilter))) expect_error(computeBounds(testy, family = "jsmurf", alpha = "s", stat = teststat, filter = testfilter)) teststatmatrix <- monteCarloSimulation(n = 36L, r = 100L, family = "jsmurf", filter = testfilter, intervalSystem = "all") teststatvector <- monteCarloSimulation(n = 36L, r = 100L, family = "jsmurf", filter = testfilter, output = "maximum", intervalSystem = "all") expect_identical(computeBounds(testy, family = "jsmurf", filter = testfilter, intervalSystem = "all", penalty = "sqrt", alpha = 0.078, stat = teststatvector), computeBounds(testy, family = "jsmurf", filter = testfilter, intervalSystem = "all", q = critVal(family = "jsmurf", filter = testfilter, intervalSystem = "all", alpha = 0.078, penalty = "sqrt", stat = teststatmatrix, n = testn))) teststatmatrix <- monteCarloSimulation(n = 36L, r = 100L, family = "jsmurfPS", filter = testfilter) teststatvector <- monteCarloSimulation(n = 36L, r = 100L, family = "jsmurfPS", filter = testfilter, output = "maximum", lengths = c(16, 32)) expect_equal(computeBounds(testy, alpha = 0.1, r = 100L, lengths = 13:17, penalty = "log", nq = 100, family = "jsmurfPS", filter = testfilter, intervalSystem = "all", options = list(simulation = "vectorIncreased", save = list(), load = list())), computeBounds(testy, lengths = 13:17, family = "jsmurfPS", filter = testfilter, intervalSystem = "all", q = critVal(n = 100, alpha = 0.1, r = 100L, lengths = 13:17, intervalSystem = "all", penalty = "log", family = "jsmurfPS", filter = testfilter, options = list(simulation = "vector", save = list(), load = list())))) testStepR <- new.env() teststat <- monteCarloSimulation(36L, r = 100L, family = "jsmurf", filter = testfilter) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, family = "jsmurf", filter = testfilter, options = list(simulation = "matrix", save = list(workspace = "matrix"), load = list(), envir = testStepR)), computeBounds(testy, alpha = 0.1, stat = teststat, family = "jsmurf", filter = testfilter, options = list())) expect_identical(get("critValStepRTab", envir = testStepR, inherits = FALSE)$stat[[1]], teststat) expect_identical(length(get("critValStepRTab", envir = testStepR, inherits = FALSE)$stat), 1L) expect_identical(critVal(36L, alpha = 0.1, r = 50L, output = "vector", family = "jsmurf", filter = testfilter, options = list(simulation = "matrix", save = list(), load = list(workspace = "matrix"), envir = testStepR)), critVal(36L, alpha = 0.1, stat = teststat, output = "vector", options = list(), family = "jsmurf", filter = testfilter)) remove(critValStepRTab, envir = testStepR) }) test_that("arguments in ... are tested and work for family jsmurf", { testn <- 27L testy <- rnorm(testn) testfilter <- lowpassFilter::lowpassFilter(type = "bessel", param = list(pole = 4L, cutoff = 0.1), sr = 1e4) expect_error(computeBounds(testy, family = "jsmurf", q = 1, filter = testfilter, std = 1)) expect_error(computeBounds(testy, family = "jsmurf", q = 1, intervalsystem = "all")) expect_error(computeBounds(testy, family = "jsmurfLR", q = 1)) expect_error(computeBounds(testy, family = "jsmurfPS", q = 1, sd = 1)) expect_error(computeBounds(testy, family = "jsmurfPS", q = 1, filter = unclass(testfilter))) expect_error(computeBounds(testy, sd = -0.1, family = "jsmurf", q = 1, filter = testfilter)) expect_identical(computeBounds(testy, family = "jsmurfPS", q = 1, filter = testfilter), computeBounds(testy, family = "jsmurfPS", q = 1, filter = testfilter, sd = sdrobnorm(testy, lag = testfilter$len + 1))) }) test_that("family 'hjsmurf' works", { testn <- 70L testy <- rnorm(testn) testq <- rep(1, testn) testfilter <- lowpassFilter::lowpassFilter(type = "bessel", param = list(pole = 4L, cutoff = 0.1), sr = 1e4) expect_error(computeBounds(family = "hjsmurf", q = testq, filter = testfilter)) expect_error(computeBounds(numeric(0), q = testq, filter = testfilter)) expect_identical(computeBounds(testy, family = "hjsmurf", q = testq, filter = testfilter), computeBounds(testy, family = "hjsmurf", intervalSystem = "dyaLen", lengths = 2^(4:6), q = testq, filter = testfilter)) expect_error(computeBounds(as.integer(testy), family = "hjsmurf", q = testq, filter = testfilter)) expect_error(computeBounds(c(testy, "s"), family = "hjsmurf", q = testq, filter = testfilter)) expect_error(computeBounds(c(rnorm(10), NA), family = "hjsmurf", q = testq, filter = testfilter)) bounds <- computeBounds(testy, family = "hjsmurf", q = testq, filter = testfilter) testIndices(bounds = bounds, indices = indicesDyaLenLengths, n = testn, lengths = 2^(4:6)) testBounds(bounds = bounds, singleBounds = singleBoundsHjsmurf, y = testy, criticalValues = testq, filter = testfilter) testStat(bounds = bounds, singleStat = singleStatHjsmurf, y = testy, criticalValues = testq, filter = testfilter) bounds <- computeBounds(testy, family = "hjsmurfSPS", q = testq, filter = testfilter) testIndices(bounds = bounds, indices = indicesDyaLenLengths, n = testn, lengths = 2^(4:6)) testBounds(bounds = bounds, singleBounds = singleBoundsHjsmurfSPS, y = testy, criticalValues = testq, filter = testfilter) testStat(bounds = bounds, singleStat = singleStatHjsmurfSPS, y = testy, criticalValues = testq, filter = testfilter) bounds <- computeBounds(testy, family = "hjsmurfLR", q = testq, filter = testfilter) testIndices(bounds = bounds, indices = indicesDyaLenLengths, n = testn, lengths = 2^(4:6)) testBounds(bounds = bounds, singleBounds = singleBoundsHjsmurfLR, y = testy, criticalValues = testq, filter = testfilter) testStat(bounds = bounds, singleStat = singleStatHjsmurfLR, y = testy, criticalValues = testq, filter = testfilter) testn <- 23L testy <- c(rnorm(10, 1, 0.23), rnorm(testn - 10, -1, 0.34)) testq <- 23:1 / 10 testfilter <- lowpassFilter::lowpassFilter(type = "bessel", param = list(pole = 6L, cutoff = 0.125), sr = 1e4) expect_identical(computeBounds(testy, family = "hjsmurf", q = testq, filter = testfilter), computeBounds(testy, family = "hjsmurf", q = testq, intervalSystem = "dyaLen", filter = testfilter)) expect_identical(computeBounds(testy, family = "hjsmurfSPS", q = testq, filter = testfilter), computeBounds(testy, family = "hjsmurfSPS", q = testq, intervalSystem = "dyaLen", filter = testfilter)) expect_identical(computeBounds(testy, family = "hjsmurfLR", q = testq, filter = testfilter), computeBounds(testy, family = "hjsmurfLR", q = testq, intervalSystem = "dyaLen", filter = testfilter)) bounds <- computeBounds(testy, family = "hjsmurf", q = testq, intervalSystem = "all", filter = testfilter) testIndices(bounds = bounds, indices = indicesAllLengths, n = testn, lengths = (testfilter$len + 2):testn) testBounds(bounds = bounds, singleBounds = singleBoundsHjsmurf, y = testy, criticalValues = testq, filter = testfilter) testStat(bounds = bounds, singleStat = singleStatHjsmurf, y = testy, criticalValues = testq, filter = testfilter) bounds <- computeBounds(testy, family = "hjsmurfSPS", q = testq, intervalSystem = "all", filter = testfilter) testIndices(bounds = bounds, indices = indicesAllLengths, n = testn, lengths = (testfilter$len + 2):testn) testBounds(bounds = bounds, singleBounds = singleBoundsHjsmurfSPS, y = testy, criticalValues = testq, filter = testfilter) testStat(bounds = bounds, singleStat = singleStatHjsmurfSPS, y = testy, criticalValues = testq, filter = testfilter) testn <- 37L testy <- c(rnorm(20, 1, 0.23), rnorm(testn - 20, -1, 0.34)) testfilter <- lowpassFilter::lowpassFilter(type = "bessel", param = list(pole = 4L, cutoff = 0.0789), sr = 1e4) testq <- 37:1 / 10 expect_identical(computeBounds(testy, family = "hjsmurf", q = testq, filter = testfilter), computeBounds(testy, family = "hjsmurf", q = testq, lengths = 2^(4:5), filter = testfilter)) expect_identical(computeBounds(testy, family = "hjsmurfSPS", q = testq, filter = testfilter), computeBounds(testy, family = "hjsmurfSPS", q = testq, lengths = 2^(4:5), filter = testfilter)) expect_identical(computeBounds(testy, family = "hjsmurfLR", q = testq, filter = testfilter), computeBounds(testy, family = "hjsmurfLR", q = testq, lengths = 2^(4:5), filter = testfilter)) testq <- 6:1 testfilter <- lowpassFilter::lowpassFilter(type = "bessel", param = list(pole = 4L, cutoff = 0.0789), sr = 1e4) bounds <- computeBounds(testy, family = "hjsmurf", q = testq, intervalSystem = "all", lengths = c(16:19, 35:36), filter = testfilter) testIndices(bounds = bounds, indices = indicesAllLengths, n = testn, lengths = c(16:19, 35:36)) testBounds(bounds = bounds, singleBounds = singleBoundsHjsmurf, y = testy, criticalValues = testq, lengths = c(16:19, 35:36), filter = testfilter) testStat(bounds = bounds, singleStat = singleStatHjsmurf, y = testy, criticalValues = testq, lengths = c(16:19, 35:36), filter = testfilter) bounds <- computeBounds(testy, family = "hjsmurfSPS", q = testq, intervalSystem = "all", lengths = c(16:19, 35:36), filter = testfilter) testIndices(bounds = bounds, indices = indicesAllLengths, n = testn, lengths = c(16:19, 35:36)) testBounds(bounds = bounds, singleBounds = singleBoundsHjsmurfSPS, y = testy, criticalValues = testq, lengths = c(16:19, 35:36), filter = testfilter) testStat(bounds = bounds, singleStat = singleStatHjsmurfSPS, y = testy, criticalValues = testq, lengths = c(16:19, 35:36), filter = testfilter) }) test_that("argument q is tested and works for family 'hjsmurf'", { testn <- 36L testy <- c(rnorm(12, 10, 0.13), rnorm(12, -10, 0.13), rnorm(12, 10, 0.13)) testfilter <- lowpassFilter::lowpassFilter(type = "bessel", param = list(pole = 4L, cutoff = 0.1), sr = 1e4) teststat <- monteCarloSimulation(n = 36L, r = 100L, family = "hjsmurf", filter = testfilter) expect_warning(ret <- computeBounds(testy, family = "hjsmurf", filter = testfilter)) expect_identical(ret, computeBounds(testy, family = "hjsmurf", filter = testfilter, alpha = 0.5)) expect_error(computeBounds(testy, q = rep(1, 7), alpha = 0.1, stat = teststat, family = "hjsmurf", filter = testfilter)) expect_error(computeBounds(testy, q = rep(1, 4), alpha = 0.1, stat = teststat, family = "hjsmurf", filter = testfilter)) expect_identical(computeBounds(testy, q = 3, family = "hjsmurf", intervalSystem = "all", lengths = c(13:23, 25:27), penalty = "sqrt", filter = testfilter), computeBounds(testy, family = "hjsmurf", intervalSystem = "all", lengths = c(13:23, 25:27), filter = testfilter, q = critVal(q = 3, family = "hjsmurf", intervalSystem = "all", lengths = c(13:23, 25:27), n = testn, penalty = "sqrt", filter = testfilter))) testq <- 1:45 attr(testq, "n") <- 45L expect_identical(computeBounds(testy, family = "hjsmurf", intervalSystem = "all", q = testq, filter = testfilter), computeBounds(testy, family = "hjsmurf", intervalSystem = "all", q = 1:36, filter = testfilter)) expect_identical(computeBounds(testy, family = "hjsmurf", intervalSystem = "all", q = 1:36, lengths = 13:23, filter = testfilter), computeBounds(testy, family = "hjsmurf", intervalSystem = "all", q = 13:23, lengths = 13:23, filter = testfilter)) ret <- computeBounds(testy, family = "hjsmurf", alpha = 0.1, stat = teststat, filter = testfilter) expect_identical(ret, computeBounds(testy, family = "hjsmurf", alpha = 0.1, stat = teststat, nq = testn, intervalSystem = "dyaLen", lengths = 2^(4:5), penalty = "weights", filter = testfilter)) expect_identical(ret, computeBounds(testy, family = "hjsmurf", filter = testfilter, q = critVal(family = "hjsmurf", alpha = 0.1, stat = teststat, n = testn, filter = testfilter))) expect_error(computeBounds(testy, family = "hjsmurf", alpha = "s", stat = teststat, filter = testfilter)) teststatmatrix <- monteCarloSimulation(n = 36L, r = 100L, family = "hjsmurf", filter = testfilter, intervalSystem = "all") teststatvector <- monteCarloSimulation(n = 36L, r = 100L, family = "hjsmurf", filter = testfilter, output = "maximum", intervalSystem = "all", penalty = "sqrt") expect_identical(computeBounds(testy, family = "hjsmurf", filter = testfilter, intervalSystem = "all", penalty = "sqrt", alpha = 0.078, stat = teststatvector), computeBounds(testy, family = "hjsmurf", filter = testfilter, intervalSystem = "all", q = critVal(family = "hjsmurf", filter = testfilter, intervalSystem = "all", alpha = 0.078, penalty = "sqrt", stat = teststatmatrix, n = testn))) teststatmatrix <- monteCarloSimulation(n = 36L, r = 100L, family = "hjsmurfSPS", filter = testfilter) teststatvector <- monteCarloSimulation(n = 36L, r = 100L, family = "hjsmurfSPS", filter = testfilter, output = "maximum", lengths = c(16, 32)) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, lengths = 13:17, penalty = "log", nq = 100, family = "hjsmurfSPS", filter = testfilter, intervalSystem = "all", options = list(simulation = "vectorIncreased", save = list(), load = list())), computeBounds(testy, lengths = 13:17, family = "hjsmurfSPS", filter = testfilter, intervalSystem = "all", q = critVal(n = 100, alpha = 0.1, r = 100L, lengths = 13:17, intervalSystem = "all", penalty = "log", family = "hjsmurfSPS", filter = testfilter, options = list(simulation = "vector", save = list(), load = list())))) testStepR <- new.env() teststat <- monteCarloSimulation(36L, r = 100L, family = "hjsmurf", filter = testfilter) expect_identical(computeBounds(testy, alpha = 0.1, r = 100L, family = "hjsmurf", filter = testfilter, options = list(simulation = "matrix", save = list(workspace = "matrix"), load = list(), envir = testStepR)), computeBounds(testy, alpha = 0.1, stat = teststat, family = "hjsmurf", filter = testfilter, options = list())) expect_identical(get("critValStepRTab", envir = testStepR, inherits = FALSE)$stat[[1]], teststat) expect_identical(length(get("critValStepRTab", envir = testStepR, inherits = FALSE)$stat), 1L) expect_identical(critVal(36L, alpha = 0.1, r = 50L, output = "vector", family = "hjsmurf", filter = testfilter, options = list(simulation = "matrix", save = list(), load = list(workspace = "matrix"), envir = testStepR)), critVal(36L, alpha = 0.1, stat = teststat, output = "vector", options = list(), family = "hjsmurf", filter = testfilter)) remove(critValStepRTab, envir = testStepR) }) test_that("arguments in ... are tested and work for family hjsmurf", { testn <- 27L testy <- rnorm(testn) testfilter <- lowpassFilter::lowpassFilter(type = "bessel", param = list(pole = 4L, cutoff = 0.1), sr = 1e4) expect_error(computeBounds(testy, family = "hjsmurf", q = 1, filter = testfilter, sd = 1)) expect_error(computeBounds(testy, family = "hjsmurf", q = 1, intervalsystem = "all")) expect_error(computeBounds(testy, family = "hjsmurfLR", q = 1)) expect_error(computeBounds(testy, family = "hjsmurfSPS", q = 1, filter = unclass(testfilter))) }) test_that("families LR and 2Param lead to errors", { testn <- 27L testy <- rnorm(testn) testfilter <- lowpassFilter::lowpassFilter(type = "bessel", param = list(pole = 4L, cutoff = 0.1), sr = 1e4) expect_error(computeBounds(testy, family = "LR", q = rep(1, testn), filter = testfilter)) expect_error(computeBounds(testy, family = "2Param", q = rep(1, testn), filter = testfilter)) })