R: Frequency Domain Based Analysis: Dynamic PCA

# Frequency Domain Based Analysis: Dynamic PCA

## Documentation for package ‘freqdom’ version 2.0.5

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

## Help Pages

freqdom-package | Frequency domain basde analysis: dynamic PCA
%c% | Convolute (filter) a multivariate time series using a time-domain filter
cov.structure | Estimate cross-covariances of two stationary multivariate time series
dpca | Compute Dynamic Principal Components and dynamic Karhunen Loeve extepansion
dpca.filters | Compute DPCA filter coefficients
dpca.KLexpansion | Dynamic KL expansion
dpca.scores | Obtain dynamic principal components scores
dpca.var | Proportion of variance explained
filter.process | Convolute (filter) a multivariate time series using a time-domain filter
fourier.inverse | Coefficients of a discrete Fourier transform
fourier.transform | Computes the Fourier transformation of a filter given as 'timedom' object
freqdom | Create an object corresponding to a frequency domain functional
freqdom.eigen | Eigendecompose a frequency domain operator at each frequency
is.freqdom | Checks if an object belongs to the class freqdom
is.timedom | Checks if an object belongs to the class timedom
rar | Simulate a multivariate autoregressive time series
rma | Moving average process
spectral.density | Compute empirical spectral density
timedom | Defines a linear filter
timedom.norms | Compute operator norms of elements of a filter
timedom.trunc | Choose lags of an object of class 'timedom'
_PACKAGE | Frequency domain basde analysis: dynamic PCA