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)
|Author||Kyoungjae Lee [aut], Lizhen Lin [ctb], Kisung You [aut, cre] (<https://orcid.org/0000-0002-8584-459X>)|
|Date of publication||2018-02-18 04:55:34 UTC|
|Maintainer||Kisung You <[email protected]>|
|License||GPL (>= 3)|
|Package repository||View on CRAN|
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