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rename vector2ratio to ratio
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@ -46,13 +46,13 @@ export(left_join_microorganisms)
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export(mo_property)
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export(mo_property)
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export(n_rsi)
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export(n_rsi)
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export(p.symbol)
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export(p.symbol)
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export(ratio)
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export(right_join_microorganisms)
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export(right_join_microorganisms)
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export(rsi)
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export(rsi)
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export(rsi_df)
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export(rsi_df)
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export(rsi_predict)
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export(rsi_predict)
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export(semi_join_microorganisms)
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export(semi_join_microorganisms)
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export(top_freq)
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export(top_freq)
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export(vector2ratio)
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exportMethods(as.double.mic)
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exportMethods(as.double.mic)
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exportMethods(as.integer.mic)
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exportMethods(as.integer.mic)
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exportMethods(as.numeric.mic)
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exportMethods(as.numeric.mic)
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6
NEWS.md
6
NEWS.md
@ -5,12 +5,12 @@
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* Possibility to globally set the default for the amount of items to print in frequency tables (`freq` function), with `options(max.print.freq = n)`
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* Possibility to globally set the default for the amount of items to print in frequency tables (`freq` function), with `options(max.print.freq = n)`
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* Functions `clipboard_import` and `clipboard_export` as helper functions to quickly copy and paste from/to software like Excel and SPSS
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* Functions `clipboard_import` and `clipboard_export` as helper functions to quickly copy and paste from/to software like Excel and SPSS
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* Function `g.test` to perform the Χ<sup>2</sup> distributed [*G*-test](https://en.wikipedia.org/wiki/G-test)
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* Function `g.test` to perform the Χ<sup>2</sup> distributed [*G*-test](https://en.wikipedia.org/wiki/G-test)
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* Function `p.symbol` to transform p value to their related symbol: `0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1`
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* Function `ratio` to transform a vector of values to a preset ratio (convenient to use with `g.test`). For example:
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* Function `vector2ratio` to transform a vector of values to a preset ratio. For example:
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```r
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```r
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vector2ratio(c(772, 1611, 737), ratio = "1:2:1")
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ratio(c(772, 1611, 737), ratio = "1:2:1")
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# [1] 780 1560 780
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# [1] 780 1560 780
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```
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```
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* Function `p.symbol` to transform p value to their related symbol: `0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1`
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#### Changed
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#### Changed
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* Frequency tables (function `freq`) now supports quasiquotation: `freq(mydata, mycolumn)`, or `mydata %>% freq(mycolumn)`
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* Frequency tables (function `freq`) now supports quasiquotation: `freq(mydata, mycolumn)`, or `mydata %>% freq(mycolumn)`
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12
R/g.test.R
12
R/g.test.R
@ -20,7 +20,7 @@
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#'
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#'
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#' A \emph{G}-test can be used to see whether the number of observations in each category fits a theoretical expectation (called a \strong{\emph{G}-test of goodness-of-fit}), or to see whether the proportions of one variable are different for different values of the other variable (called a \strong{\emph{G}-test of independence}).
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#' A \emph{G}-test can be used to see whether the number of observations in each category fits a theoretical expectation (called a \strong{\emph{G}-test of goodness-of-fit}), or to see whether the proportions of one variable are different for different values of the other variable (called a \strong{\emph{G}-test of independence}).
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#' @param x numeric vector or matrix
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#' @param x numeric vector or matrix
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#' @param y expected value of \code{x}. Leave empty to determine automatically. This can also be ratios of \code{x}, e.g. calculated with \code{\link{vector2ratio}}.
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#' @param y expected value of \code{x}. Leave empty to determine automatically. This can also be ratios of \code{x}, e.g. calculated with \code{\link{ratio}}.
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#' @param alpha value to test the p value against
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#' @param alpha value to test the p value against
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#' @param info logical to determine whether the analysis should be printed
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#' @param info logical to determine whether the analysis should be printed
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#' @param minimum the test with fail if any of the observed values is below this value. Use \code{minimum = 30} for microbial epidemiology, to prevent calculating a p value when less than 30 isolates are available.
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#' @param minimum the test with fail if any of the observed values is below this value. Use \code{minimum = 30} for microbial epidemiology, to prevent calculating a p value when less than 30 isolates are available.
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@ -70,7 +70,7 @@
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#' # ratio.
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#' # ratio.
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#'
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#'
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#' x <- c(772, 1611, 737)
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#' x <- c(772, 1611, 737)
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#' x.expected <- vector2ratio(x, ratio = "1:2:1")
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#' x.expected <- ratio(x, "1:2:1")
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#' x.expected
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#' x.expected
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#' # 780 1560 780
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#' # 780 1560 780
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#'
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#'
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@ -90,7 +90,7 @@
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#' # observed 1752 right-billed and 1895 left-billed crossbills.
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#' # observed 1752 right-billed and 1895 left-billed crossbills.
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#'
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#'
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#' x <- c(1752, 1895)
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#' x <- c(1752, 1895)
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#' x.expected <- vector2ratio(x, ratio = c(1, 1))
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#' x.expected <- ratio(x, ratio = c(1, 1))
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#' x.expected
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#' x.expected
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#' # 1823.5 1823.5
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#' # 1823.5 1823.5
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#'
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#'
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@ -215,7 +215,7 @@ g.test <- function(x,
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#' # ratio.
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#' # ratio.
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#'
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#'
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#' x <- c(772, 1611, 737)
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#' x <- c(772, 1611, 737)
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#' x.expected <- vector2ratio(x, ratio = "1:2:1")
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#' x.expected <- ratio(x, "1:2:1")
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#' x.expected
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#' x.expected
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#' # 780 1560 780
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#' # 780 1560 780
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#'
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#'
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@ -235,7 +235,7 @@ g.test <- function(x,
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#' # observed 1752 right-billed and 1895 left-billed crossbills.
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#' # observed 1752 right-billed and 1895 left-billed crossbills.
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#'
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#'
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#' x <- c(1752, 1895)
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#' x <- c(1752, 1895)
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#' x.expected <- vector2ratio(x, ratio = c(1, 1))
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#' x.expected <- ratio(x, ratio = c(1, 1))
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#' x.expected
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#' x.expected
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#' # 1823.5 1823.5
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#' # 1823.5 1823.5
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#'
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#'
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@ -245,7 +245,7 @@ g.test <- function(x,
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#' # There is a significant difference from a 1:1 ratio.
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#' # There is a significant difference from a 1:1 ratio.
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#' # Meaning: there are significantly more left-billed birds.
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#' # Meaning: there are significantly more left-billed birds.
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#'
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#'
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vector2ratio <- function(x, ratio) {
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ratio <- function(x, ratio) {
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if (!all(is.numeric(x))) {
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if (!all(is.numeric(x))) {
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stop('`x` must be a vector of numeric values.')
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stop('`x` must be a vector of numeric values.')
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}
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}
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@ -9,7 +9,7 @@ g.test(x, y = NULL, alpha = 0.05, info = TRUE, minimum = 0)
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\arguments{
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\arguments{
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\item{x}{numeric vector or matrix}
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\item{x}{numeric vector or matrix}
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\item{y}{expected value of \code{x}. Leave empty to determine automatically. This can also be ratios of \code{x}, e.g. calculated with \code{\link{vector2ratio}}.}
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\item{y}{expected value of \code{x}. Leave empty to determine automatically. This can also be ratios of \code{x}, e.g. calculated with \code{\link{ratio}}.}
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\item{alpha}{value to test the p value against}
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\item{alpha}{value to test the p value against}
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@ -68,7 +68,7 @@ If there are more than two categories and you want to find out which ones are si
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# ratio.
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# ratio.
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x <- c(772, 1611, 737)
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x <- c(772, 1611, 737)
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x.expected <- vector2ratio(x, ratio = "1:2:1")
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x.expected <- ratio(x, "1:2:1")
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x.expected
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x.expected
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# 780 1560 780
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# 780 1560 780
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@ -88,7 +88,7 @@ g.test(x, x.expected)
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# observed 1752 right-billed and 1895 left-billed crossbills.
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# observed 1752 right-billed and 1895 left-billed crossbills.
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x <- c(1752, 1895)
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x <- c(1752, 1895)
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x.expected <- vector2ratio(x, ratio = c(1, 1))
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x.expected <- ratio(x, ratio = c(1, 1))
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x.expected
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x.expected
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# 1823.5 1823.5
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# 1823.5 1823.5
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@ -1,10 +1,10 @@
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% Generated by roxygen2: do not edit by hand
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% Generated by roxygen2: do not edit by hand
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% Please edit documentation in R/g.test.R
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% Please edit documentation in R/g.test.R
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\name{vector2ratio}
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\name{ratio}
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\alias{vector2ratio}
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\alias{ratio}
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\title{Transform vector to ratio}
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\title{Transform vector to ratio}
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\usage{
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\usage{
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vector2ratio(x, ratio)
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ratio(x, ratio)
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}
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}
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\arguments{
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\arguments{
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\item{x}{vector of values}
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\item{x}{vector of values}
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@ -25,7 +25,7 @@ Transform vector to ratio
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# ratio.
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# ratio.
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x <- c(772, 1611, 737)
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x <- c(772, 1611, 737)
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x.expected <- vector2ratio(x, ratio = "1:2:1")
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x.expected <- ratio(x, "1:2:1")
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x.expected
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x.expected
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# 780 1560 780
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# 780 1560 780
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@ -45,7 +45,7 @@ g.test(x, x.expected)
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# observed 1752 right-billed and 1895 left-billed crossbills.
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# observed 1752 right-billed and 1895 left-billed crossbills.
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x <- c(1752, 1895)
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x <- c(1752, 1895)
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x.expected <- vector2ratio(x, ratio = c(1, 1))
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x.expected <- ratio(x, ratio = c(1, 1))
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x.expected
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x.expected
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# 1823.5 1823.5
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# 1823.5 1823.5
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@ -6,14 +6,14 @@ test_that("G-test works", {
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# example 1: clearfield rice vs. red rice
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# example 1: clearfield rice vs. red rice
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x <- c(772, 1611, 737)
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x <- c(772, 1611, 737)
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x.expected <- vector2ratio(x, ratio = "1:2:1")
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x.expected <- ratio(x, ratio = "1:2:1")
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expect_equal(g.test(x, x.expected),
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expect_equal(g.test(x, x.expected),
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expected = 0.12574,
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expected = 0.12574,
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tolerance = 0.00001)
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tolerance = 0.00001)
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# example 2: red crossbills
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# example 2: red crossbills
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x <- c(1752, 1895)
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x <- c(1752, 1895)
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x.expected <- vector2ratio(x, ratio = c(1, 1))
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x.expected <- ratio(x, ratio = c(1, 1))
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expect_equal(g.test(x, x.expected),
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expect_equal(g.test(x, x.expected),
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expected = 0.01787343,
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expected = 0.01787343,
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tolerance = 0.00000001)
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tolerance = 0.00000001)
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