zeitzeigerSpc: Calculate sparse principal components of time-dependent...

Description Usage Arguments Value See Also

View source: R/zeitzeiger_fit.R

Description

zeitzeigerSpc calculates the sparse principal components (SPCs), given the time-dependent means and the residuals from zeitzeigerFit. This function calls PMA::SPC.

Usage

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zeitzeigerSpc(xFitMean, xFitResid, nTime = 10, useSpc = TRUE, sumabsv = 1,
  orth = TRUE, ...)

Arguments

xFitMean

List of bigsplines, length is number of features.

xFitResid

Matrix of residuals, dimensions are observations by features.

nTime

Number of time-points by which to discretize the time-dependent behavior of each feature. Corresponds to the number of rows in the matrix for which the SPCs will be calculated.

useSpc

Logical indicating whether to use SPC (default) or svd.

sumabsv

L1-constraint on the SPCs, passed to SPC.

orth

Logical indicating whether to require left singular vectors be orthogonal to each other, passed to SPC.

...

Other arguments passed to SPC.

Value

Result from SPC, unless useSpc==FALSE, then result from svd.

See Also

zeitzeigerFit, zeitzeigerPredict


jakejh/zeitzeiger documentation built on Nov. 22, 2017, 2:06 a.m.