runPCA: Perform an Principal Component Analysis

Description Usage Arguments Value Author(s) See Also Examples

View source: R/pca.R

Description

This function performs a Principal Component Analysis (PCA) and represents the samples or the variables of the analysis.

Usage

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runPCA(X, ncp=5, scale=TRUE, ind.sup=NULL, quanti.sup=NULL,quali.sup=NULL,
sample.qual=TRUE, variable.qual=FALSE, sample.cont=TRUE,variable.cont=FALSE,
plotSample=TRUE, plotVariable=FALSE, plotInertia = TRUE, plotBiplot=FALSE,
lab.sample="quality", lab.var=NULL,palette="rainbow",
lim.cos2.sample=0, lim.cos2.var=0, pdf=FALSE, pdfname= NULL, verbose=FALSE, ...) 

Arguments

X

a data frame with n rows (samples) and p columns (variables)

ncp

number of dimensions kept in the results (by default 5)

scale

a boolean, if TRUE (value set by default) then data are scaled to unit variance

ind.sup

a vector indicating the indexes of the supplementary individuals

quanti.sup

a vector indicating the indexes of the quantitative supplementary variables

quali.sup

a vector indicating the indexes of the qualitative supplementary variables

sample.qual

a boolean, if TRUE quality sample is displayed, by default = TRUE

variable.qual

a boolean, if TRUE quality variable is displayed, by default = FALSE

sample.cont

a boolean, if TRUE sample contribution is displayed, by default = TRUE

variable.cont

a boolean, if TRUE variable contribution is displayed, by default = FALSE

plotSample

a boolean, if TRUE samples are displayed, by default = TRUE

plotVariable

a boolean, if TRUE variables are displayed, by default = FALSE

plotInertia

a boolean, if TRUE inertia percentage of components is displayed, by default = TRUE

plotBiplot

a boolean, if TRUE biplot is displayed, by default = FALSE

lab.sample

a vector, sample representation is colored by label.sample, by default = NULL

lab.var

a vector, variable representation is colored by label.var, by default = "quality"

palette

character, name of palette color, by default = "rainbow"

lim.cos2.sample

a numeric, for graphics, keep samples with cos2 >= lim.cos2.sample, by default = 0

lim.cos2.var

a numeric, for graphics, keep variables with cos2 >= lim.cos2.var, by default = 0

pdf

a boolean, if TRUE save all the graphics in a pdf file, by default = FALSE

pdfname

pdf file name for saving graphics

verbose

print results if verbose = TRUE, by default = FALSE

...

Arguments to be passed to methods, such as graphical parameters (see 'par').

Value

eig

a matrix containing all the eigenvalues, the percentage of variance and the cumulative percentage of variance

var

a list of matrices containing all the results for the active variables (coordinates, correlation between variables and axes, square cosine, contributions

ind

a list of matrices containing all the results for the active individuals (coordinates, square cosine, contributions)

Returns the individuals factor map for axes 1 and 2, 1 and 3, 2 and 3 Returns the inertia percentage of components By default, print sample coordinates, sample quality and sample contribution

Author(s)

Nicolas Servant, Eleonore Gravier, Pierre Gestraud, Cecile Laurent, Caroline Paccard, Anne Biton, Jonas Mandel, Bernard Asselain, Emmanuel Barillot, Philippe Hupe

See Also

plotSample, plotVariable, plotInertia

Examples

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data("marty")

## PCA on sample with inertia plot and sample plot colored by tumour type

example.subset <- marty[1:100,]
pca <- runPCA(t(example.subset), verbose = FALSE, lab.sample = marty.type.cl)

EMA documentation built on May 29, 2017, 1:39 p.m.