Package: MVNtestchar
Type: Package
Title: Multivariate Normal Distribution Characterization Test
Version: 1.0.0
Date: 2020-03-21
Authors@R: person("William", "Fairweather", email = "wrf343@flowervalleyconsulting.com",
    role = c("aut", "cre"))
Description: Provides a test of multivariate normality of a sample which does
    not require estimation of the nuisance parameters, the mean and covariance 
    matrix.  Rather, a sequence of transformations removes these nuisance 
    parameters and results in a set of sample matrices that are positive 
    definite.  These matrices are uniformly distributed on the space of positive 
    definite matrices in the unit hyperrectangle if and only if the original 
    data is multivariate normal. The package performs a goodness of fit test of 
    this hypothesis. Four sample datasets are included: a bivariate and a
    trivariate normal set and a bivariate and trivariate Bernoulli set. In 
    addition to the test, functions in the package give rotatable visualizations 
    of the support region of positive definite matrices for bivariate samples.
Depends: R (>= 2.10)
Imports: graphics, grDevices, Hmisc, stats, utils
License: GPL (>= 2)
NeedsCompilation: no
Packaged: 2020-03-27 17:57:47 UTC; No
Author: William Fairweather [aut, cre]
Maintainer: William Fairweather <wrf343@flowervalleyconsulting.com>
Repository: CRAN
Date/Publication: 2020-03-30 14:20:02 UTC
