Functional Time Series: Dynamic Functional Principal Components

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Documentation for package ‘freqdom.fda’ version 1.0.1

• DESCRIPTION file.
• Code demos. Use demo() to run them.

Help Pages

freqdom.fda-package	Functional time series: dynamic FPCA
fda.ts	Functional time series: dynamic FPCA
fts.cov.structure	Estimate autocovariance and cross-covariances operators
fts.dpca	Compute Functional Dynamic Principal Components and dynamic Karhunen Loeve extepansion
fts.dpca.filters	Functional dynamic PCA filters
fts.dpca.KLexpansion	Dynamic KL expansion
fts.dpca.scores	Functional dynamic principal component scores
fts.dpca.var	Proportion of variance explained by dynamic principal components
fts.freqdom	Creates an object of class 'fts.freqdom'.
fts.plot.covariance	Contour plot for the kernels of cross-covariance operators.
fts.plot.filters	Plot kernels
fts.plot.operators	Contour plot of operator kernels.
fts.rar	Simulate functional autoregressive processes
fts.rma	Simulate functional moving average processes
fts.spectral.density	Functional spectral and cross-spectral density operator
fts.timedom	Object of class 'fts.timedom'
is.fts.freqdom	Checks if an object belongs to the class fts.freqdom
is.fts.timedom	Checks if an object belongs to the class fts.timedom
pm10	PM10 dataset
_PACKAGE	Functional time series: dynamic FPCA