covsep
Tests for Determining if the Covariance Structure of 2-Dimensional Data is Separable
Functions for testing if the covariance structure of 2-dimensional data (e.g. samples of surfaces X_i = X_i(s,t)) is separable, i.e. if covariance(X) = C_1 x C_2. A complete descriptions of the implemented tests can be found in the paper Aston, John A. D.; Pigoli, Davide; Tavakoli, Shahin. Tests for separability in nonparametric covariance operators of random surfaces. Ann. Statist. 45 (2017), no. 4, 1431–1461. doi:10.1214/16-AOS1495 https://projecteuclid.org/euclid.aos/1498636862 doi:10.48550/arXiv.1505.02023.
- Version1.1.0
- R versionunknown
- LicenseGPL-2
- Needs compilation?No
- Last release05/06/2018
Team
Shahin Tavakoli
Davide Pigoli
Show author detailsRolesContributorJohn Aston
Show author detailsRolesContributor
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Last 30 days
This package has been downloaded 164 times in the last 30 days. Now we're getting somewhere! Enough downloads to populate a lively group chat. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 8 times.
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Last 365 days
This package has been downloaded 2,011 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 Jul 24, 2024 with 25 downloads.
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- Imports1 package