Nonparametric Estimation of Toeplitz Covariance Matrices R package vstdct version 0.2 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), <arXiv:2303.10018>. Software Depends: R (>= 3.5.0) Imports: dtt, MASS, nlme Suggests: testthat (>= 3.0.0) Karolina Klockmann <karolina.klockmann@gmx.de> Comprehensive R Archive Network (CRAN) Karolina Klockmann [aut, cre], Tatyana Krivobokova [aut] GPL-2 2023-07-06 application/tgz https://CRAN.R-project.org/package=vstdct doi:10.32614/CRAN.package.vstdct