R2VX-pcaRes-method: R2 goodness of fit
In pcaMethods: A collection of PCA methods

Description Usage Arguments Value Author(s) Examples

Flexible calculation of R2 goodness of fit.

## S4 method for signature 'pcaRes'
R2VX(object, direction = c("variables",
  "observations", "complete"), data = completeObs(object),
  pcs = nP(object))

`object`	a PCA model object
`direction`	choose between calculating R2 per variable, per observation or for the entire data with 'variables', 'observations' or 'complete'.
`data`	the data used to fit the model
`pcs`	the number of PCs to use to calculate R2

A vector with R2 values

Henning Redestig

1	R2VX(pca(iris))

Loading required package: Biobase
Loading required package: BiocGenerics
Loading required package: parallel

Attaching package: 'BiocGenerics'

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    clusterApply, clusterApplyLB, clusterCall, clusterEvalQ,
    clusterExport, clusterMap, parApply, parCapply, parLapply,
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The following objects are masked from 'package:stats':

    IQR, mad, sd, var, xtabs

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    intersect, is.unsorted, lapply, lengths, mapply, match, mget,
    order, paste, pmax, pmax.int, pmin, pmin.int, rank, rbind,
    rowMeans, rowSums, rownames, sapply, setdiff, sort, table, tapply,
    union, unique, unsplit, which, which.max, which.min

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Attaching package: 'pcaMethods'

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

    loadings

Sepal.Length  Sepal.Width Petal.Length  Petal.Width 
   0.9579017    0.8400028    0.9980931    0.9365937