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) manifold wavelet regression and clustering for curves of Hermitian positive definite matrices, and (ii) exploratory data analysis and inference for samples of (curves of) Hermitian positive definite matrices by means of manifold data depth and manifold rank-based hypothesis tests.

Maintainer: Joris Chau <j.chau at uclouvain.be>

Author(s): Joris Chau*

Install package and any missing dependencies by running this line in your R console:

install.packages("pdSpecEst")

Depends R (>= 3.3.1)
Imports astsa, multitaper, Rcpp, ddalpha
Suggests knitr, rmarkdown, testthat
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Linking to Rcpp, RcppArmadillo(>=0.7.500.0.0)
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Package pdSpecEst
Materials
URL https://github.com/JorisChau/pdSpecEst https://jchau.shinyapps.io/pdspecest/
Task Views
Version 1.1.1
Published 2017-07-02
License GPL (>= 2)
BugReports
SystemRequirements GNU make, C++11
NeedsCompilation yes
Citation
CRAN checks pdSpecEst check results
Package source pdSpecEst_1.1.1.tar.gz