pdSpecEst: An Analysis Toolbox for Hermitian Positive Definite Matrices

An implementation of data analysis tools for samples of symmetric or Hermitian positive definite matrices, such as collections of covariance matrices or spectral density matrices. The tools in this package can be used to perform: (i) intrinsic wavelet transforms for curves (1D) or surfaces (2D) of Hermitian positive definite matrices with applications to dimension reduction, denoising and clustering in the space of Hermitian positive definite matrices; and (ii) exploratory data analysis and inference for samples of positive definite matrices by means of intrinsic data depth functions and rank-based hypothesis tests in the space of Hermitian positive definite matrices.

Version: 1.2.4
Depends: R (≥ 3.4.0)
Imports: multitaper, Rcpp, ddalpha, Rdpack
LinkingTo: Rcpp, RcppArmadillo (≥ 0.7.500.0.0)
Suggests: knitr, rmarkdown, testthat, grid, ggplot2, reshape2, viridis, ggthemes
Published: 2020-01-08
Author: Joris Chau [aut, cre]
Maintainer: Joris Chau <joris.chau at openanalytics.eu>
License: GPL-2
URL: https://github.com/JorisChau/pdSpecEst
NeedsCompilation: yes
SystemRequirements: GNU make, C++11
Materials: README NEWS
CRAN checks: pdSpecEst results

Documentation:

Reference manual: pdSpecEst.pdf
Vignettes: "Data depth and rank-based tests for HPD matrices"
"Wavelet-based multivariate Fourier spectral estimation"

Downloads:

Package source: pdSpecEst_1.2.4.tar.gz
Windows binaries: r-devel: pdSpecEst_1.2.4.zip, r-release: pdSpecEst_1.2.4.zip, r-oldrel: pdSpecEst_1.2.4.zip
macOS binaries: r-release (arm64): pdSpecEst_1.2.4.tgz, r-oldrel (arm64): pdSpecEst_1.2.4.tgz, r-release (x86_64): pdSpecEst_1.2.4.tgz
Old sources: pdSpecEst archive

Linking:

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