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(v1.5.0.9006) major documentation update

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dr. M.S. (Matthijs) Berends
2021-01-18 16:57:56 +01:00
parent e95218c0d1
commit 4eab095306
174 changed files with 1488 additions and 1071 deletions
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5
R/pca.R
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@ -26,7 +26,7 @@
#' Principal Component Analysis (for AMR)
#'
#' Performs a principal component analysis (PCA) based on a data set with automatic determination for afterwards plotting the groups and labels, and automatic filtering on only suitable (i.e. non-empty and numeric) variables.
#' @inheritSection lifecycle Maturing lifecycle
#' @inheritSection lifecycle Maturing Lifecycle
#' @param x a [data.frame] containing numeric columns
#' @param ... columns of `x` to be selected for PCA, can be unquoted since it supports quasiquotation.
#' @inheritParams stats::prcomp
@ -36,6 +36,7 @@
#' @return An object of classes [pca] and [prcomp]
#' @importFrom stats prcomp
#' @export
#' @inheritSection AMR Read more on Our Website!
#' @examples
#' # `example_isolates` is a dataset available in the AMR package.
#' # See ?example_isolates.
@ -98,7 +99,7 @@ pca <- function(x,
x <- as.data.frame(new_list, stringsAsFactors = FALSE)
if (any(vapply(FUN.VALUE = logical(1), x, function(y) !is.numeric(y)))) {
warning_("Be sure to first calculate the resistance (or susceptibility) of variables with antimicrobial test results, since PCA works with numeric variables only. Please see Examples in ?pca.")
warning_("Be sure to first calculate the resistance (or susceptibility) of variables with antimicrobial test results, since PCA works with numeric variables only. See Examples in ?pca.")
}
# set column names