doi:10.1081/STA-120025379>, including random vector generation and explicit estimators of the location vector and scale matrix. The package implements kernel density estimators discussed in Belzile, Desgagnes, Genest and Ouimet (2024) <doi:10.48550/arXiv.2209.04757> for smoothing multivariate data on half-spaces.">

mig: Multivariate Inverse Gaussian Distribution (original) (raw)

Provides utilities for estimation for the multivariate inverse Gaussian distribution of Minami (2003) <doi:10.1081/STA-120025379>, including random vector generation and explicit estimators of the location vector and scale matrix. The package implements kernel density estimators discussed in Belzile, Desgagnes, Genest and Ouimet (2024) <doi:10.48550/arXiv.2209.04757> for smoothing multivariate data on half-spaces.

Version: 2.0
Depends: R (≥ 2.10)
Imports: statmod, TruncatedNormal (≥ 2.3), Rcpp (≥ 1.0.12)
LinkingTo: Rcpp, RcppArmadillo
Suggests: numDeriv, tinytest, knitr, rmarkdown, minqa
Published: 2025-04-08
DOI: 10.32614/CRAN.package.mig
Author: Leo Belzile ORCID iD [aut, cre], Frederic Ouimet ORCID iD [aut]
Maintainer: Leo Belzile
BugReports: https://github.com/lbelzile/mig/issues
License: MIT + file
NeedsCompilation: yes
Materials: README, NEWS
In views: Distributions
CRAN checks: mig results

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