Extract leverages of a PCA model

Description

The leverages of PCA model indicate how much influence each observation has on the PCA model. Observations with high leverage has caused the principal components to rotate towards them. It can be used to extract both "unimportant" observations as well as picking potential outliers.

Usage

## S4 method for signature 'pcaRes'
leverage(object)

Arguments

Details

Defined as Tr(T(T'T)^(-1)T')

Value

The observation leverages as a numeric vector

Author(s)

Henning Redestig

References

Introduction to Multi- and Megavariate Data Analysis using Projection Methods (PCA and PLS), L. Eriksson, E. Johansson, N. Kettaneh-Wold and S. Wold, Umetrics 1999, p. 466

Examples

data(iris)
pcIr <- pca(iris[,1:4])
## versicolor has the lowest leverage
with(iris, plot(leverage(pcIr)~Species))

Results

R version 3.3.1 (2016-06-21) -- "Bug in Your Hair"
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> library(pcaMethods)
Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

The following objects are masked from 'package:parallel':

    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
    parLapplyLB, parRapply, parSapply, parSapplyLB

The following objects are masked from 'package:stats':

    IQR, mad, xtabs

The following objects are masked from 'package:base':

    Filter, Find, Map, Position, Reduce, anyDuplicated, append,
    as.data.frame, cbind, colnames, do.call, duplicated, eval, evalq,
    get, grep, grepl, intersect, is.unsorted, lapply, lengths, mapply,
    match, mget, order, paste, pmax, pmax.int, pmin, pmin.int, rank,
    rbind, rownames, sapply, setdiff, sort, table, tapply, union,
    unique, unsplit

Welcome to Bioconductor

    Vignettes contain introductory material; view with
    'browseVignettes()'. To cite Bioconductor, see
    'citation("Biobase")', and for packages 'citation("pkgname")'.


Attaching package: 'pcaMethods'

The following object is masked from 'package:stats':

    loadings

> png(filename="/home/ddbj/snapshot/RGM3/R_BC/result/pcaMethods/leverage-pcaRes-method.Rd_%03d_medium.png", width=480, height=480)
> ### Name: leverage,pcaRes-method
> ### Title: Extract leverages of a PCA model
> ### Aliases: leverage leverage,pcaRes-method
> ### Keywords: multivariate
> 
> ### ** Examples
> 
> data(iris)
> pcIr <- pca(iris[,1:4])
> ## versicolor has the lowest leverage
> with(iris, plot(leverage(pcIr)~Species))
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>