A nonparametric method to estimate Toeplitz covariance matrices from a sample of n independently and identically distributed p-dimensional vectors with mean zero. The data is preprocessed with the discrete cosine matrix and a variance stabilization transformation to obtain an approximate Gaussian regression setting for the log-spectral density function. Estimates of the spectral density function and the inverse of the covariance matrix are provided as well. Functions for simulating data and a protein data example are included. For details see (Klockmann, Krivobokova; 2023), <doi:10.48550/arXiv.2303.10018>.
Version: 0.2 Depends: R (≥ 3.5.0) Imports: dtt, MASS, nlme Suggests: testthat (≥ 3.0.0) Published: 2023-07-06 DOI: 10.32614/CRAN.package.vstdct Author: Karolina Klockmann [aut, cre], Tatyana Krivobokova [aut] Maintainer: Karolina Klockmann <karolina.klockmann at gmx.de> License: GPL-2 NeedsCompilation: no CRAN checks: vstdct results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=vstdct to link to this page.
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