test_that("Posterior calculation for composites works", { counts <- c(1, 2, 3) expect_equal(stbp_posterior_composite(data = counts, greater_than = TRUE, hypothesis = 2, density_func = "poisson", prior = 0.5, lower_bnd = 0, upper_bnd = Inf), 0.60630278) }) test_that("Posterior calculation for composites works", { counts <- c(1, 2, 3) expect_equal(stbp_posterior_composite(data = counts, greater_than = TRUE, hypothesis = 2, density_func = "negative binomial", overdispersion = 2, prior = 0.5, lower_bnd = 0, upper_bnd = Inf), 0.72558593) }) test_that("STBP for composites works", { set.seed(101) counts3 <- rpois(5, lambda = 3) expect_equal(stbp_composite(data = counts3, greater_than = TRUE, hypothesis = 5, density_func = "poisson", prior = 0.5, lower_bnd = 0, upper_bnd = Inf, lower_criterion = 0.001, upper_criterion = 0.999)@recommendation, "reject H") }) test_that("STBP for composites works", { set.seed(101) counts3 <- rpois(5, lambda = 3) expect_equal(stbp_composite(data = counts3, greater_than = TRUE, hypothesis = 5, density_func = "poisson", prior = 0.5, lower_bnd = 0, upper_bnd = Inf, lower_criterion = 0.001, upper_criterion = 0.999)@iterations, 2) }) test_that("STBP for composites works", { H <- c(2, 5, 10, 20, 40, 40, 20, 10, 5, 2) countP <- matrix(NA, 3, 10) set.seed(101) for(i in 1:10){ countP[, i] <- rpois(3, lambda = (H[i] - 1)) } expect_equal(stbp_composite(data = countP, greater_than = TRUE, hypothesis = H, density_func = "poisson", prior = 0.5, lower_bnd = 0, upper_bnd = Inf, lower_criterion = 0.001, upper_criterion = 0.999)@recommendation, "reject H") }) test_that("STBP for composites works", { H <- c(2, 5, 10, 20, 40, 40, 20, 10, 5, 2) countP <- matrix(NA, 3, 10) set.seed(101) for(i in 1:10){ countP[, i] <- rpois(3, lambda = (H[i] - 1)) } expect_equal(stbp_composite(data = countP, greater_than = TRUE, hypothesis = H, density_func = "poisson", prior = 0.5, lower_bnd = 0, upper_bnd = Inf, lower_criterion = 0.001, upper_criterion = 0.999)@iterations, 8) }) test_that("STBP for composites works (binomial data)", { set.seed(101) counts4 <- list() for(i in 1: 7) { counts4[[i]] <- matrix(c(rbinom(5, size = 10, prob = 0.25), rep(10, 5)), 5, 2) } expect_equal(stbp_composite(data = counts4, greater_than = TRUE, hypothesis = 0.2, density_func = "binomial", prior = 0.5, lower_bnd = 0, upper_bnd = 1, lower_criterion = 0.001, upper_criterion = 0.999)@recommendation, "accept H") }) test_that("STBP for composites works (binomial data)", { set.seed(101) counts4 <- list() for(i in 1: 7) { counts4[[i]] <- matrix(c(rbinom(5, size = 10, prob = 0.25), rep(10, 5)), 5, 2) } expect_equal(stbp_composite(data = counts4, greater_than = TRUE, hypothesis = 0.2, density_func = "binomial", prior = 0.5, lower_bnd = 0, upper_bnd = 1, lower_criterion = 0.001, upper_criterion = 0.999)@iterations, 3) }) test_that("Posterior calculation for simples works", { counts <- c(0, 0, 0) expect_equal(stbp_posterior_simple(data = counts, density_func = "poisson", prior = 0.5, upper_bnd = Inf), 0.75) }) test_that("STBP for simples works", { counts10 <- matrix(rep(0, 30), 10, 3) expect_equal(stbp_simple(data = counts10, density_func = "poisson", prior = 0.5, upper_bnd = Inf, lower_criterion = 0, upper_criterion = 0.9999)@recommendation, "keep sampling") }) test_that("STBP for simples works", { counts10 <- matrix(rep(0, 30), 10, 3) expect_equal(stbp_simple(data = counts10, density_func = "poisson", prior = 0.5, upper_bnd = Inf, lower_criterion = 0, upper_criterion = 0.9999)@iterations, 3) }) test_that("STBP for simples works", { counts30 <- matrix(rep(0, 90), 30, 3) expect_equal(stbp_simple(data = counts30, density_func = "poisson", prior = 0.5, upper_bnd = Inf, lower_criterion = 0, upper_criterion = 0.9999)@recommendation, "accept H") }) test_that("STBP for simples works", { counts30 <- matrix(rep(0, 90), 30, 3) expect_equal(stbp_simple(data = counts30, density_func= "poisson", prior = 0.5, upper_bnd = Inf, lower_criterion = 0, upper_criterion = 0.9999)@iterations, 3) })