test_that("chisq_gof equal to chisq.test", {
x <- c(14, 18, 12, 58)
p <- c(0.2, 0.2, 0.2, 0.4)
set.seed(40)
a <- chisq_gof(x, p)$p.value
set.seed(40)
b <- chisq.test(x, p = p, simulate.p.value = TRUE, B = 10000)$p.value
expect_equal(a, b)
})
test_that("chisq_gof equal to chisq.test", {
x <- c(134, 128)
p <- c(0.6, 0.4)
set.seed(40)
a <- chisq_gof(x, p)$p.value
set.seed(40)
b <- chisq.test(x, p = p, simulate.p.value = TRUE, B = 10000)$p.value
expect_equal(a, b)
})
test_that("chisq_gof equal to rms_gof for uniform distribution", {
x <- c(14, 18, 12, 13, 15)
p <- c(0.2, 0.2, 0.2, 0.2, 0.2)
set.seed(40)
a <- chisq_gof(x, p)$p.value
set.seed(40)
b <- rms_gof(x, p)$p.value
expect_equal(a, b)
})
skip_on_cran()
test_that("rms_gof is equal to stored result", {
x <- c(2114, 2128, 2112)
p <- c(rep(1/3, 3))
set.seed(40)
a <- rms_gof(x, p)$p.value
b <- 0.966903309669033
expect_equal(a, b)
})
test_that("ks_gof ~equal to ks.test (from dgof package)", {
x <- c(14, 18, 15, 28)
xx <- c(rep(1, 14), rep(2, 18), rep(3, 15), rep(4, 28))
y <- c(1, 2, 3, 4, 4)
p <- c(0.2, 0.2, 0.2, 0.4)
set.seed(284)
a <- ks_gof(x, p, reps = 2000)$p.value
set.seed(284)
b <- dgof::ks.test(xx, ecdf(y), simulate.p.value = TRUE, B = 2000)$p.value
expect_equal(tolerance = 0.01, a, b)
})
test_that("g_gof is asymtoptically equal to chisq_gof", {
x <- c(2114, 2128, 2112)
p <- c(rep(1/3, 3))
set.seed(300)
a <- chisq_gof(x, p)$p.value
set.seed(300)
b <- g_gof(x, p)$p.value
expect_equal(a, b)
})
test_that("g_gof is ~equal to G.test (from RVAideMemoire package)", {
x <- c(214, 228, 212)
p <- c(rep(1/3, 3))
set.seed(30)
a <- g_gof(x, p)$p.value
b <- 0.707378226223282
#b <- as.numeric(RVAideMemoire::G.test(x, p)$p.value)
expect_equal(tolerance = 0.001, a, b)
})
test_that("ft_gof is asymtoptically equal to chisq_gof", {
x <- c(2114, 2128, 2112)
p <- c(rep(1/3, 3))
set.seed(300)
a <- chisq_gof(x, p)$p.value
set.seed(300)
b <- ft_gof(x, p)$p.value
expect_equal(a, b)
})
test_that("cvm_gof ~equal to groupFit (from cvmdisc package)", {
x <- c(14, 18, 15, 28)
p <- c(0.2, 0.2, 0.2, 0.4)
breaks <- c(0, cumsum(p))
set.seed(4180)
a <- cvm_gof(x, p, reps = 10000)$p.value
set.seed(4180)
b <- cvmdisc::groupFit(breaks, x, distr = "unif", bootstrap = TRUE, numLoops = 10000)$pvals[2, 1]
expect_equal(tolerance = 0.01, a, b)
})
test_that("cvm_gof ~equal to cvm.test (from dgof package)", {
x <- c(1, 4, 11, 4, 0)
p <- c(0.05, 0.3, 0.3, 0.3, 0.05)
set.seed(10)
a <- cvm_gof(x, p, reps = 10000)$p.value
#xx <- c(rep(1, 1), rep(2, 4), rep(3, 11), rep(4, 4), rep(5, 0))
#pp <- c(rep(1, 1), rep(2, 6), rep(3, 6), rep(4, 6), rep(5, 1))
#b <- dgof::cvm.test(xx, ecdf(pp))$p.value
b <- 0.243733
expect_equal(tolerance = 0.015, a, b)
})
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