Package: MDgof
Title: Various Methods for the Goodness-of-Fit Problem in D>1
        Dimensions
Version: 1.0.0
Authors@R: 
        person("Wolfgang", "Rolke", , "wolfgang.rolke@upr.edu", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0002-3514-726X"))
Description: The routine gof_test() in this package runs the
    goodness-of-fit test using various test statistic for multivariate data. 
    Models under the null hypothesis can either be simple or allow for parameter estimation.
    p values are found via the parametric bootstrap (simulation). 
    The routine gof_test_adjusted_pvalues() runs several tests and then finds a 
    p value adjusted for simultaneous inference.
    The routine gof_power() allows the estimation of the power of the tests. 
    hybrid_test() and hybrid_power() do the same by first generating a Monte Carlo data set under
    the null hypothesis and then running a number of two-sample methods.
    The routine run.studies() allows a user to quickly study the power of a new method and 
    how it compares to those included in the package via a large number of case studies.
    For details of the methods and references see the included vignettes.      
License: GPL (>= 2)
Encoding: UTF-8
RoxygenNote: 7.3.3
LinkingTo: Rcpp
Imports: Rcpp, parallel, stats, microbenchmark, spatstat.geom,
        spatstat.explore, FNN, copula, mvtnorm, ggplot2,
        microbenchmark, MD2sample
Suggests: rmarkdown, knitr
VignetteBuilder: knitr
Depends: R (>= 3.5)
LazyData: true
NeedsCompilation: yes
Packaged: 2026-02-10 13:00:15 UTC; Wolfgang
Author: Wolfgang Rolke [aut, cre] (ORCID:
    <https://orcid.org/0000-0002-3514-726X>)
Maintainer: Wolfgang Rolke <wolfgang.rolke@upr.edu>
Repository: CRAN
Date/Publication: 2026-02-12 20:40:03 UTC
