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freqdom (version 2.0.5)

Frequency Domain Based Analysis: Dynamic PCA

Description

Implementation of dynamic principal component analysis (DPCA), simulation of VAR and VMA processes and frequency domain tools. These frequency domain methods for dimensionality reduction of multivariate time series were introduced by David Brillinger in his book Time Series (1974). We follow implementation guidelines as described in Hormann, Kidzinski and Hallin (2016), Dynamic Functional Principal Component .

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Version

Install

install.packages('freqdom')

Monthly Downloads

493

Version

2.0.5

License

GPL-3

Maintainer

Lukasz Kidzinski

Last Published

April 6th, 2024

Functions in freqdom (2.0.5)

rar

Simulate a multivariate autoregressive time series
rma

Moving average process
freqdom

Create an object corresponding to a frequency domain functional
summary.freqdom

Print object summary
spectral.density

Compute empirical spectral density
freqdom.eigen

Eigendecompose a frequency domain operator at each frequency
freqdom.product

Compute a matrix product of two frequency-domain operators
rev.timedom

rev Reverts order of lags in an object of class timedom
print.timedom

Print timedom object
rev

Invert order of lags or grid parameters of a timedom or freqdom object, respectively
freqdom.transpose

Compute a transpose of a given frequency-domain operator at each frequency
plus.freqdom

Frequency-wise sum of freqdom objects
+.timedom

Time-wise sum of freqdom objects
print.freqdom

Print freqdom object
timedom.norms

Compute operator norms of elements of a filter
timedom.trunc

Choose lags of an object of class timedom
summary.timedom

Print object summary
timedom

Defines a linear filter
filter.process

Convolute (filter) a multivariate time series using a time-domain filter
dpca

Compute Dynamic Principal Components and dynamic Karhunen Loeve extepansion
-.freqdom

Frequency-wise difference of freqdom objects
fourier.inverse

Coefficients of a discrete Fourier transform
-.timedom

Time-wise difference of freqdom objects
%*%

Frequency-wise product of freqdom objects
dpca.scores

Obtain dynamic principal components scores
dpca.var

Proportion of variance explained
cov.structure

Estimate cross-covariances of two stationary multivariate time series
dpca.filters

Compute DPCA filter coefficients
freqdom-package

Frequency domain basde analysis: dynamic PCA
fourier.transform

Computes the Fourier transformation of a filter given as timedom object
dpca.KLexpansion

Dynamic KL expansion
+.freqdom

Frequency-wise sum of freqdom objects
is.timedom

Checks if an object belongs to the class timedom
is.freqdom

Checks if an object belongs to the class freqdom