Covariance is of universal prevalence across various disciplines within statistics. We provide a rich collection of geometric and inferential tools for convenient analysis of covariance structures, topics including distance measures, mean covariance estimator, covariance hypothesis test for one-sample and two-sample cases, and covariance estimation. For an introduction to covariance in multivariate statistical analysis, see Schervish (1987) <doi:10.1214/ss/1177013111>.
Version: | 0.3.0 |
Depends: | R (≥ 2.14.0) |
Imports: | Rcpp, geigen, shapes, expm, mvtnorm, stats, Matrix, doParallel, foreach, parallel, pracma, Rdpack |
LinkingTo: | Rcpp, RcppArmadillo |
Published: | 2018-02-18 |
Author: | Kyoungjae Lee [aut],
Lizhen Lin [ctb],
Kisung You |
Maintainer: | Kisung You <kyou at nd.edu> |
License: | GPL (≥ 3) |
NeedsCompilation: | yes |
CRAN checks: | CovTools results |
Reference manual: | CovTools.pdf |
Package source: | CovTools_0.3.0.tar.gz |
Windows binaries: | r-devel: CovTools_0.3.0.zip, r-release: CovTools_0.3.0.zip, r-oldrel: CovTools_0.3.0.zip |
OS X El Capitan binaries: | r-release: CovTools_0.3.0.tgz |
OS X Mavericks binaries: | r-oldrel: CovTools_0.2.1.tgz |
Old sources: | CovTools archive |
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