sfaPBootstrap

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

realclass

matrix containing the training data

list with several parameter settings, e.g. as created by <code><a rd-options="" href="/link/sfa2Create?package=rSFA&version=1.5" data-mini-rdoc="rSFA::sfa2Create">sfa2Create</a></code>
<code>sfaList$xpDimFun</code> (=xpDim by default) calculated dimension of expaned SFA space
<code>sfaList$deg</code> degree of expansion (should not be 1, not implemented)
<code>sfaList$ppRange</code> ppRange for SFA algorithm
<code>sfaList$nclass</code> number of unique classes
<code>sfaList$doPB</code> do (1) or do no (0) param. bootstrap.

sfaList

If training set too small, augment it with parametric bootstrap

Slow Feature Analysis (SFA), ported to R based on
'matlab' implementations of SFA: 'SFA toolkit' 1.0 by Pietro Berkes and 'SFA toolkit'
2.8 by Wolfgang Konen.

Martin Zaefferer

rSFA

Slow Feature Analysis

sfaPBootstrap function

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

sfaPBootstrap: Parametric Bootstrap

Description

Usage

Arguments

Value

See Also