mirror of https://github.com/msberends/AMR.git
74 lines
3.0 KiB
R
74 lines
3.0 KiB
R
# ==================================================================== #
|
|
# TITLE #
|
|
# AMR: An R Package for Working with Antimicrobial Resistance Data #
|
|
# #
|
|
# SOURCE #
|
|
# https://github.com/msberends/AMR #
|
|
# #
|
|
# CITE AS #
|
|
# Berends MS, Luz CF, Friedrich AW, Sinha BNM, Albers CJ, Glasner C #
|
|
# (2022). AMR: An R Package for Working with Antimicrobial Resistance #
|
|
# Data. Journal of Statistical Software, 104(3), 1-31. #
|
|
# doi:10.18637/jss.v104.i03 #
|
|
# #
|
|
# Developed at the University of Groningen, the Netherlands, in #
|
|
# collaboration with non-profit organisations Certe Medical #
|
|
# Diagnostics & Advice, and University Medical Center Groningen. #
|
|
# #
|
|
# 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. #
|
|
# #
|
|
# Visit our website for the full manual and a complete tutorial about #
|
|
# how to conduct AMR data analysis: https://msberends.github.io/AMR/ #
|
|
# ==================================================================== #
|
|
|
|
# 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))$p.value,
|
|
0.12574,
|
|
tolerance = 0.0001
|
|
)
|
|
|
|
# example 2: red crossbills
|
|
x <- c(1752, 1895)
|
|
expect_equal(g.test(x)$p.value,
|
|
0.017873,
|
|
tolerance = 0.0001
|
|
)
|
|
|
|
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))
|
|
|
|
# INDEPENDENCE
|
|
|
|
x <- as.data.frame(
|
|
matrix(
|
|
data = round(runif(4) * 100000, 0),
|
|
ncol = 2,
|
|
byrow = TRUE
|
|
)
|
|
)
|
|
|
|
# fisher.test() is always better for 2x2 tables:
|
|
expect_warning(g.test(x))
|
|
expect_true(suppressWarnings(g.test(x)$p.value) < 1)
|
|
|
|
expect_warning(g.test(
|
|
x = c(772, 1611, 737),
|
|
y = c(780, 1560, 780),
|
|
rescale.p = TRUE
|
|
))
|
|
|
|
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)))
|