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 121 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 2 times.
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Last 365 days
This package has been downloaded 1,789 times in the last 365 days. Consider this 'mid-tier influencer' status—if it were a TikTok, it would get a nod from nieces and nephews. The day with the most downloads was Sep 11, 2024 with 23 downloads.
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Dependencies
- Imports3 packages
- Suggests1 package