AMR/inst/tinytest/test-g.test.R

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# ==================================================================== #
# TITLE: #
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# AMR: An R Package for Working with Antimicrobial Resistance Data #
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# #
# SOURCE CODE: #
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# https://github.com/msberends/AMR #
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# #
# PLEASE CITE THIS SOFTWARE AS: #
# Berends MS, Luz CF, Friedrich AW, et al. (2022). #
# AMR: An R Package for Working with Antimicrobial Resistance Data. #
# Journal of Statistical Software, 104(3), 1-31. #
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# https://doi.org/10.18637/jss.v104.i03 #
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# #
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# Developed at the University of Groningen and the University Medical #
# Center Groningen in The Netherlands, in collaboration with many #
# colleagues from around the world, see our website. #
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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 data analysis: https://msberends.github.io/AMR/ #
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# ==================================================================== #
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# GOODNESS-OF-FIT
# example 1: clearfield rice vs. red rice
x <- c(772, 1611, 737)
expect_equal(g.test(x, p = c(0.25, 0.50, 0.25))$p.value,
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0.12574,
tolerance = 0.0001
)
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# example 2: red crossbills
x <- c(1752, 1895)
expect_equal(g.test(x)$p.value,
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0.017873,
tolerance = 0.0001
)
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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(
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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))
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expect_true(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)))