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(v2.1.1.9232) is.mic() iteration, documentation cleanup
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R/pca.R
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R/pca.R
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#' Principal Component Analysis (for AMR)
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#'
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#' 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.
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#' @param x a [data.frame] containing [numeric] columns
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#' @param ... columns of `x` to be selected for PCA, can be unquoted since it supports quasiquotation.
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#' @param x A [data.frame] containing [numeric] columns
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#' @param ... Columns of `x` to be selected for PCA, can be unquoted since it supports quasiquotation.
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#' @inheritParams stats::prcomp
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#' @details The [pca()] function takes a [data.frame] as input and performs the actual PCA with the \R function [prcomp()].
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#'
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