MVT: Estimation and testing for the multivariate t-distribution

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. The package uses these functions in algorithms to simulate, analyze, and fit the model to data. The methodology is described, with examples, in the following paper.


Providing Feedback

Please report any bugs/suggestions/improvements to Felipe Osorio, Universidad Técnica Federico Santa María. If you find these routines useful or not then please let me know. Also, acknowledgement of the use of the routines is appreciated.


Latest binaries and sources for MVT are available from CRAN package repository .

Installation instructions

To install this package, start R and enter:


Alternatively, 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)


Next, you can load the package by using the command: library(MVT)

To cite the MVT package in publications use:

Osorio, F. (2023). Estimation and testing for the multivariate t-distribution. R package version 0.3-8,


Osorio, F., Galea, M., Henríquez, C., Arellano-Valle, R. (2023). Addressing non-normality in multivariate analysis using the t-distribution. AStA Advances in Statistical Analysis , doi: 10.1007/s10182-022-00468-2.

Some papers using MVT:

About the Author

I'm Assistant Professor at Department of Mathematics of the Universidad Técnica Federico Santa María, Chile.

I contribute as developer/maintainer of the following R packages: