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big website update, licence txt update

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dr. M.S. (Matthijs) Berends
2019-01-02 23:24:07 +01:00
parent 4255707cb7
commit 6b2d464f8c
190 changed files with 8785 additions and 66176 deletions
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man/g.test.Rd
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@@ -100,6 +100,12 @@ where \code{df} are the degrees of freedom.
If there are more than two categories and you want to find out which ones are significantly different from their null expectation, you can use the same method of testing each category vs. the sum of all categories, with the Bonferroni correction. You use \emph{G}-tests for each category, of course.
}
\section{Read more on our website!}{
\if{html}{\figure{logo.png}{options: height=40px style=margin-bottom:5px} \cr}
On our website \url{https://msberends.gitlab.io/AMR} you can find \href{https://msberends.gitlab.io/AMR/articles/AMR.html}{a omprehensive tutorial} about how to conduct AMR analysis and find \href{https://msberends.gitlab.io/AMR/reference}{the complete documentation of all functions}, which reads a lot easier than in R.
}
\examples{
# = EXAMPLE 1 =
# Shivrain et al. (2006) crossed clearfield rice (which are resistant
@@ -110,7 +116,7 @@ If there are more than two categories and you want to find out which ones are si
# by a single gene with two co-dominant alleles, you would expect a 1:2:1
# ratio.
x <- c(772, 1611, 737)#'
x <- c(772, 1611, 737)
G <- g.test(x, p = c(1, 2, 1) / 4)
# G$p.value = 0.12574.