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> <arXiv:1505.02023>.

Version: 1.1.0
Depends: R (≥ 3.2.3)
Imports: mvtnorm (≥ 1.0.4)
Published: 2018-05-06
Author: Shahin Tavakoli [aut, cre], Davide Pigoli [ctb], John Aston [ctb]
Maintainer: Shahin Tavakoli <s.tavakoli at warwick.ac.uk>
License: GPL-2
URL: http://arxiv.org/abs/1505.02023
NeedsCompilation: no
In views: FunctionalData
CRAN checks: covsep results

Downloads:

Reference manual: covsep.pdf
Package source: covsep_1.1.0.tar.gz
Windows binaries: r-devel: covsep_1.1.0.zip, r-devel-gcc8: covsep_1.1.0.zip, r-release: covsep_1.1.0.zip, r-oldrel: covsep_1.1.0.zip
OS X binaries: r-release: covsep_1.1.0.tgz, r-oldrel: covsep_1.1.0.tgz
Old sources: covsep archive

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