Package: MVNtestchar
Type: Package
Title: Test for Multivariate Normal Distribution Based on a
        Characterization
Version: 1.1.3
Date: 2020-07-14
Authors@R: person("William", "Fairweather", email = "wrf343@flowervalleyconsulting.com",
    role = c("aut", "cre"))
Description: Provides a test of multivariate normality of an unknown sample 
    that 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 
    hyper-rectangle if and only if the original data is multivariate normal (Fairweather,
    1973, Doctoral dissertation, University of Washington). The package performs a 
    goodness of fit test of this hypothesis. In addition to the test, functions in the 
    package give visualizations of the support region of positive definite matrices for 
    bivariate samples.
Depends: R (>= 2.10)
Imports: graphics, grDevices, Hmisc, stats, utils, knitr, ggplot2
License: GPL (>= 2)
NeedsCompilation: no
Suggests: markdown
VignetteBuilder: knitr, markdown
Packaged: 2020-07-22 15:10:07 UTC; No
Author: William Fairweather [aut, cre]
Maintainer: William Fairweather <wrf343@flowervalleyconsulting.com>
Repository: CRAN
Date/Publication: 2020-07-25 21:30:26 UTC
Built: R 4.2.0; ; 2022-04-13 17:11:05 UTC; unix
