Functional Principal Component Analysis Bandwidth Diagnostics plot

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Description

This function by default creates the mean and first principal modes of variation plots for 50 If provided with a derivative options object (?FPCAder) it will return the differentiated mean and first two principal modes of variations for 50

Usage

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CreateBWPlot(fpcaObj, derOptns = NULL, bwMultipliers = NULL)

Arguments

fpcaObj

An FPCA class object returned by FPCA().

derOptns

A list of options to control the derivation parameters; see ?FPCAder. If NULL standard diagnostics are returned

bwMultipliers

A vector of multipliers that the original 'bwMu' and 'bwCov' will be multiplied by. (default: c(0.50, 0.75, 1.00, 1.25, 1.50)) - default: NULL

Examples

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set.seed(1)
n <- 20
pts <- seq(0, 1, by=0.05)
sampWiener <- Wiener(n, pts)
sampWiener <- Sparsify(sampWiener, pts, 10)
res1 <- FPCA(sampWiener$Ly, sampWiener$Lt, 
            list(dataType='Sparse', error=FALSE, kernel='epan', verbose=FALSE))
CreateBWPlot(res1)

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