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>.
|Author||Kyoungjae Lee [aut], Lizhen Lin [ctb], Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)|
|Maintainer||Kisung You <email@example.com>|
|License||GPL (>= 3)|
|Package repository||View on CRAN|
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