sfaPBootstrap {rSFA}

Parametric Bootstrap

Description

If training set too small, augment it with parametric bootstrap

Usage

sfaPBootstrap(realclass, x, sfaList)

Arguments

realclass

true class of training data (can be vector, numerics, integers, factors)

x

matrix containing the training data

sfaList

list with several parameter settings, e.g. as created by sfa2Create
sfaList$xpDimFun (=xpDim by default) calculated dimension of expaned SFA space
sfaList$deg degree of expansion (should not be 1, not implemented)
sfaList$ppRange ppRange for SFA algorithm
sfaList$nclass number of unique classes
sfaList$doPB do (1) or do no (0) param. bootstrap.

Value

a list list containing:

x

training set extended to minimu number of recors1.5*(xpdim+nclass), if necessary

realclass

training class labels, extended analogously

See Also

addNoisyCopies