vstdct
Nonparametric Estimation of Toeplitz Covariance Matrices
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>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2 |
rolling linux/jammy R-4.5 | vstdct_0.2.tar.gz |
175.0 KiB |
0.2 |
rolling linux/noble R-4.5 | vstdct_0.2.tar.gz |
175.0 KiB |
0.2 |
rolling source/ R- | vstdct_0.2.tar.gz |
140.5 KiB |
0.2 |
latest linux/jammy R-4.5 | vstdct_0.2.tar.gz |
175.0 KiB |
0.2 |
latest linux/noble R-4.5 | vstdct_0.2.tar.gz |
175.0 KiB |
0.2 |
latest source/ R- | vstdct_0.2.tar.gz |
140.5 KiB |
0.2 |
2026-04-26 source/ R- | vstdct_0.2.tar.gz |
140.5 KiB |
0.2 |
2026-04-23 source/ R- | vstdct_0.2.tar.gz |
140.5 KiB |
0.2 |
2026-04-09 windows/windows R-4.5 | vstdct_0.2.zip |
180.6 KiB |
0.2 |
2025-04-20 source/ R- | vstdct_0.2.tar.gz |
140.5 KiB |