InPosition (version 1.0.0)

epPCA.inference.battery: epPCA.inference.battery: Inference tests for Principal Component Analysis (PCA) via InPosition.

Description

Principal Component Analysis (PCA) and a battery of inference tests via InPosition. The battery includes permutation and bootstrap tests.

Usage

epPCA.inference.battery(
  DATA,
  scale = TRUE,
  center = TRUE,
  DESIGN = NULL,
  make_design_nominal = TRUE,
  graphs = TRUE,
  k = 0,
  test.iters = 100,
  constrained = FALSE,
  critical.value = 2
)

Value

Returns two lists ($Fixed.Data and $Inference.Data). For $Fixed.Data, see epPCA, corePCA for details on the descriptive (fixed-effects) results.

$Inference.Data returns:

components

Permutation tests of components. p-values ($p.vals) and distributions of eigenvalues ($eigs.perm) for each component

fj.boots

Bootstrap tests of measures (columns). See boot.ratio.test output details.

Arguments

DATA

original data to perform a PCA on.

scale

a boolean, vector, or string. See expo.scale for details.

center

a boolean, vector, or string. See expo.scale for details.

DESIGN

a design matrix to indicate if rows belong to groups.

make_design_nominal

a boolean. If TRUE (default), DESIGN is a vector that indicates groups (and will be dummy-coded). If FALSE, DESIGN is a dummy-coded matrix.

graphs

a boolean. If TRUE (default), graphs and plots are provided (via epGraphs)

k

number of components to return.

test.iters

number of iterations

constrained

a boolean. If a DESIGN matrix is used, this will constrain bootstrap resampling to be within groups.

critical.value

numeric. A value, analogous to a z- or t-score to be used to determine significance (via bootstrap ratio).

Author

Derek Beaton and Hervé Abdi.

Details

epPCA.inference.battery performs principal components analysis and inference tests on a data matrix.

If the expected time to compute the results (based on test.iters) exceeds 1 minute, you will be asked (via command line) if you want to continue.

See Also

epPCA

Examples

	data(words)
	pca.words.res <- epPCA.inference.battery(words$data)