DModX

Description

Distance to the model of X-space.

Usage

DModX(object, dat, newdata=FALSE, type=c("normalized","absolute"), ...)

Arguments

Details

Measures how well described the observations are, i.e. how well they fit in the mode. High DModX indicate a poor fit. Defined as:

frac{√{frac{SSE_i}{K-A}}}{√{frac{SSE}{(N-A-A_0)(K-A)}}}

For observation i, in a model with A components, K variables and N obserations. SSE is the squared sum of the residuals. A_0 is 1 if model was centered and 0 otherwise. DModX is claimed to be approximately F-distributed and can therefore be used to check if an observation is significantly far away from the PCA model assuming normally distributed data.

Pass original data as an argument if the model was calculated with completeObs=FALSE.

Value

A vector with distances from observations to the PCA model

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. 468

Examples

data(iris)
pcIr <- pca(iris[,1:4])
with(iris, plot(DModX(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/DModX-pcaRes-method.Rd_%03d_medium.png", width=480, height=480)
> ### Name: DModX,pcaRes-method
> ### Title: DModX
> ### Aliases: DModX DModX,pcaRes-method
> 
> ### ** Examples
> 
> data(iris)
> pcIr <- pca(iris[,1:4])
> with(iris, plot(DModX(pcIr)~Species))
> 
> 
> 
> 
> 
> dev.off()
null device 
          1 
>