{"id":32626239,"url":"https://github.com/faosorios/mvt","last_synced_at":"2026-06-28T20:31:53.774Z","repository":{"id":282975659,"uuid":"950282767","full_name":"faosorios/MVT","owner":"faosorios","description":"Estimation and testing for the multivariate t-distribution","archived":false,"fork":false,"pushed_at":"2026-02-27T18:54:52.000Z","size":60,"stargazers_count":0,"open_issues_count":0,"forks_count":0,"subscribers_count":1,"default_branch":"main","last_synced_at":"2026-02-27T22:59:53.381Z","etag":null,"topics":["envelope","equicorrelation-test","homogeneity-test","kurtosis","multivariate-analysis","multivariate-t","student-t-distribution","wilson-hilferty-transformation"],"latest_commit_sha":null,"homepage":"https://cran.r-project.org/package=MVT","language":"C","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/faosorios.png","metadata":{"files":{"readme":"README.md","changelog":"ChangeLog","contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2025-03-17T23:20:53.000Z","updated_at":"2026-02-27T18:54:56.000Z","dependencies_parsed_at":"2025-03-18T00:28:38.558Z","dependency_job_id":"17620e76-c6b5-4a39-99b5-b02166238d38","html_url":"https://github.com/faosorios/MVT","commit_stats":null,"previous_names":["faosorios/mvt"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/faosorios/MVT","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/faosorios%2FMVT","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/faosorios%2FMVT/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/faosorios%2FMVT/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/faosorios%2FMVT/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/faosorios","download_url":"https://codeload.github.com/faosorios/MVT/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/faosorios%2FMVT/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34903523,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-28T02:00:05.809Z","response_time":54,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["envelope","equicorrelation-test","homogeneity-test","kurtosis","multivariate-analysis","multivariate-t","student-t-distribution","wilson-hilferty-transformation"],"created_at":"2025-10-30T20:59:47.627Z","updated_at":"2026-06-28T20:31:53.769Z","avatar_url":"https://github.com/faosorios.png","language":"C","funding_links":[],"categories":[],"sub_categories":[],"readme":"# MVT: Estimation and testing for the multivariate t-distribution\n\n\u003c!-- badges: start --\u003e\n[![CRAN status](http://www.r-pkg.org/badges/version/MVT)](https://cran.r-project.org/package=MVT)\n![CRAN/METACRAN](https://img.shields.io/cran/l/MVT?color=informational)\n![GitHub last commit](https://img.shields.io/github/last-commit/faosorios/MVT)\n[![CRAN RStudio mirror downloads](http://cranlogs.r-pkg.org/badges/MVT)](https://cran.r-project.org/package=MVT)\n\u003c!-- badges: end --\u003e\n\n`MVT` package contains a set of routines to perform estimation and inference under the multivariate t-distribution. These methods are a direct generalization of the multivariate inference under the gaussian assumption. In addition, these procedures provide robust methods useful against outliers.\n\n## Resources\n\nLatest binaries and sources can be found at the [CRAN package repository](https://cran.r-project.org/package=MVT):\n\n* [MVT_0.3-81.tar.gz](https://cran.r-project.org/src/contrib/MVT_0.3-81.tar.gz) - Package sources\n* [MVT_0.3-81.zip](https://cran.r-project.org/bin/windows/contrib/4.4/MVT_0.3-81.zip) - Windows binaries (R-release)\n* [MVT_0.3-81.tgz](https://cran.r-project.org/bin/macosx/big-sur-arm64/contrib/4.4/MVT_0.3-81.tgz) - MacOS binaries (R-release, arm64)\n* [MVT_0.3-81.tgz](https://cran.r-project.org/bin/macosx/big-sur-x86_64/contrib/4.4/MVT_0.3-81.tgz) - MacOS binaries (R-release, x86_64)\n\n## Reference Manual\n\n* [PDF manual](https://cran.r-project.org/web/packages/MVT/MVT.pdf) | [HTML manual](https://cran.r-project.org/web/packages/MVT/refman/MVT.html)\n\n## Features\n\n-   Basic functionality for modeling using the multivariate t-distribution.\n-   Estimation of mean, covariance matrix and the shape (kurtosis) parameter using the EM algorithm.\n-   The core routines have been implemented in C and linked to R to ensure a reasonable computational speed.\n-   Performs hypothesis testing about the equicorrelation or homogeneity of variances structures for the covariance matrix, considering the test statistics of likelihood ratio, score, Wald or gradient.\n-   Multivariate random number generation for the multivariate t- (and gaussian) distribution.\n-   Graphical methods for assessing the assumption of multivariate t- (and gaussian) distribution.\n\n## Installation instructions\n\nInstall `MVT` from CRAN using.\n\n``` r\ninstall.packages(\"MVT\")\n```\nYou can install the latest development version from github with:\n\n``` r\n# install.packages(\"devtools\")\ndevtools::install_github(\"faosorios/MVT\")\n```\nAlternatively, you can download the source as a tarball or as a zip file. Unpack the tarball or zipfile (thereby creating a directory named, MVT) and install the package source by executing (at the console prompt)\n\n``` r\nR CMD INSTALL MVT\n```\nNext, you can load the package by using the command `library(MVT)`\n\n## Providing Feedback\n\nPlease report any bugs/suggestions/improvements to [Felipe Osorio](https://faosorios.github.io/). If you find these routines useful or not then please let me know. Also, acknowledgement of the use of the routines is appreciated.\n\n### To cite package `MVT` in publications use:\n``` r\ncitation(\"MVT\")\n\nTo cite MVT package in publications use:\n \n  Osorio, F. (2024). Estimation and testing for the multivariate\n  t-distribution. R package version 0.3-81. URL:\n  http://mvt.mat.utfsm.cl\n \nA BibTeX entry for LaTeX users is\n \n  @Manual{,\n   title = {Estimation and testing for the multivariate t-distribution},\n   author = {F. Osorio},\n   year = {2024},\n   note = {R package version 0.3-81},\n   url = {https://github.com/faosorios/MVT},\n  }\n```\n\n## Reference\n\nOsorio, F., Galea, M., Henriquez, C., Arellano-Valle, R. (2023). Addressing non-normality in multivariate analysis using the t-distribution. [AStA Advances in Statistical Analysis](https://doi.org/10.1007/s10182-022-00468-2) 107, 785-813.\n\n## Papers using MVT\n- de Freitas, J.V.B, Bondon, P., Azevedo, C.L.N., Reisen, V.A., Nobre, J.S. (2024). Scale mixtures of multivariate centered skew-normal distributions. [Statistics and Computing](https://doi.org/10.1007/s11222-024-10512-7) 34, 212.\n- Mignemi, G., Panzeri, A., Granziol, U., Bruno, G., Bertamini, M., Vidotto, G., Spoto, A. (2023). The mediating role of scientifical-medical satisfaction between COVID-19 conspiracy beliefs and vaccine confidence: A two-waves structural equation model. [Journal of Behavioral Medicine](https://doi.org/10.1007/s10865-022-00322-5) 46, 201-211\n- Hintz, E., Hofert, M., Lemieux, C. (2022). Multivariate Normal Variance Mixtures in R: The R Package nvmix. [Journal of Statistical Software](https://doi.org/10.18637/jss.v102.i02) 102, 1-31.\n- Punzo, A., Bagnato, L. (2020). Allometric analysis using the multivariate shifted exponential normal distribution. [Biometrical Journal](https://doi.org/10.1002/bimj.201900248) 62, 1525-1543.\n\n## About the Author\n\nFelipe Osorio is an applied statistician and creator of several R packages. Webpage: [faosorios.github.io](https://faosorios.github.io/)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffaosorios%2Fmvt","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Ffaosorios%2Fmvt","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Ffaosorios%2Fmvt/lists"}