context("cpit()") # simulate data set.seed(3) x <- matrix(rnorm(30), 10, 3) y <- x %*% c(1, -1, 2) dat <- data.frame(y = y, x = x, z = as.factor(rbinom(10, 3, 0.5))) fit <- vinereg(y ~ ., family = "gauss", dat) test_that("catches missing variables", { expect_error(cpit(fit, dat[1:2])) }) test_that("catches incorrect type", { dat[2] <- ordered(1:10) expect_error(cpit(fit, dat)) }) test_that("catches incorrect levels", { levels(dat[[5]]) <- 1:50 expect_error(cpit(fit, dat)) }) test_that("works in bivariate case", { fit <- vinereg(y ~ ., dat[1:2]) expect_silent(cpit(fit, dat[1:2])) }) test_that("works with continuous response", { expect_gt(ks.test(cpit(fit, dat), "punif")$p, 0.01) }) test_that("works with discrete response", { dat$y <- as.ordered(dat$y) fit <- vinereg(y ~ ., dat, fam = "tll") expect_silent(cpit(fit, dat)) }) test_that("works on uscale", { dat[] <- runif(nrow(dat) * ncol(dat)) fit <- vinereg(y ~ ., dat, uscale = TRUE) p <- cpit(fit, dat) expect_true(all(p >= 0 & p <= 1)) }) context("cll()") # simulate data set.seed(3) x <- matrix(rnorm(30), 10, 3) y <- x %*% c(1, -1, 2) dat <- data.frame(y = y, x = x, z = as.factor(rbinom(10, 3, 0.5))) fit <- vinereg(y ~ ., family = "gauss", dat) test_that("catches missing variables", { expect_error(cll(fit, dat[1:2])) }) test_that("catches incorrect type", { dat[2] <- ordered(1:10) expect_error(cll(fit, dat)) }) test_that("catches incorrect levels", { levels(dat[[5]]) <- 1:50 expect_error(cll(fit, dat)) }) test_that("works in bivariate case", { fit <- vinereg(y ~ ., dat[1:2]) expect_equal(cll(fit, dat[1:2]), fit$stats$cll) }) test_that("works with continuous response", { expect_equal(cll(fit, dat), fit$stats$cll, 0.1) }) test_that("works with discrete response", { dat$y <- as.ordered(round(dat$y)) fit <- vinereg(y ~ ., dat, fam = "gauss") expect_equal(cll(fit, dat), fit$stats$cll, 5) # very lenient for now }) test_that("works on uscale", { dat[] <- runif(nrow(dat) * ncol(dat)) fit <- vinereg(y ~ ., dat, uscale = TRUE) expect_equal(cll(fit, dat), fit$stats$cll) })