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), doi:10.48550/arXiv.2303.10018.
- Version0.2
- R version≥ 3.5.0
- LicenseGPL-2
- Needs compilation?No
- Last release07/06/2023
Team
Karolina Klockmann
Tatyana Krivobokova
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Last 30 days
This package has been downloaded 119 times in the last 30 days. More than a random curiosity, but not quite a blockbuster. Still, it's gaining traction! The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 1 times.
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Last 365 days
This package has been downloaded 1,775 times in the last 365 days. Now we’re talking! This work is officially 'heard of in academic circles', just like those wild research papers on synthetic bananas. The day with the most downloads was Sep 11, 2024 with 23 downloads.
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- Imports3 packages
- Suggests1 package