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AMR/tests/testthat/test-g.test.R

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# ==================================================================== #
# TITLE #
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# Antimicrobial Resistance (AMR) Analysis for R #
# #
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# SOURCE #
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# https://github.com/msberends/AMR #
# #
# LICENCE #
# (c) 2018-2020 Berends MS, Luz CF et al. #
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# Developed at the University of Groningen, the Netherlands, in #
# collaboration with non-profit organisations Certe Medical #
# Diagnostics & Advice, and University Medical Center Groningen. #
# #
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# This R package is free software; you can freely use and distribute #
# it for both personal and commercial purposes under the terms of the #
# GNU General Public License version 2.0 (GNU GPL-2), as published by #
# the Free Software Foundation. #
# We created this package for both routine data analysis and academic #
# research and it was publicly released in the hope that it will be #
# useful, but it comes WITHOUT ANY WARRANTY OR LIABILITY. #
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# #
# Visit our website for the full manual and a complete tutorial about #
# how to conduct AMR analysis: https://msberends.github.io/AMR/ #
# ==================================================================== #
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context("g.test.R")
test_that("G-test works", {
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skip_on_cran()
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# GOODNESS-OF-FIT
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# example 1: clearfield rice vs. red rice
x <- c(772, 1611, 737)
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expect_equal(g.test(x, p = c(0.25, 0.50, 0.25))$p.value,
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expected = 0.12574,
tolerance = 0.00001)
# example 2: red crossbills
x <- c(1752, 1895)
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expect_equal(g.test(x)$p.value,
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expected = 0.01787343,
tolerance = 0.00000001)
expect_error(g.test(0))
expect_error(g.test(c(0, 1), 0))
expect_error(g.test(c(1, 2, 3, 4), p = c(0.25, 0.25)))
expect_error(g.test(c(1, 2, 3, 4), p = c(0.25, 0.25, 0.25, 0.24)))
expect_warning(g.test(c(1, 2, 3, 4), p = c(0.25, 0.25, 0.25, 0.24), rescale.p = TRUE))
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# INDEPENDENCE
x <- as.data.frame(
matrix(data = round(runif(4) * 100000, 0),
ncol = 2,
byrow = TRUE)
)
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# fisher.test() is always better for 2x2 tables:
expect_warning(g.test(x))
expect_lt(suppressWarnings(g.test(x)$p.value),
1)
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expect_warning(g.test(x = c(772, 1611, 737),
y = c(780, 1560, 780),
rescale.p = TRUE))
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expect_error(g.test(matrix(data = c(-1, -2, -3, -4), ncol = 2, byrow = TRUE)))
expect_error(g.test(matrix(data = c(0, 0, 0, 0), ncol = 2, byrow = TRUE)))
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})