matrixdist: An R Package for Statistical Analysis of Matrix Distributions

TL;DR

The paper introduces the matrixdist R package, offering comprehensive tools for statistical analysis of various matrix distributions, including estimation, regression, and practical applications in actuarial science.

Contribution

It presents a new R package that implements estimation, regression, and modeling techniques for matrix distributions, filling a gap in statistical software tools.

Findings

Provides estimation algorithms for matrix distributions.

Includes regression models like proportional intensities.

Demonstrates practical applications in actuarial problems.

Abstract

The matrixdist R package provides a comprehensive suite of tools for the statistical analysis of matrix distributions, including phase-type, inhomogeneous phase-type, discrete phase-type, and related multivariate distributions. This paper introduces the package and its key features, including the estimation of these distributions and their extensions through expectation-maximisation algorithms, as well as the implementation of regression through the proportional intensities and mixture-of-experts models. Additionally, the paper provides an overview of the theoretical background, discusses the algorithms and methods implemented in the package, and offers practical examples to illustrate the application of matrixdist in real-world actuarial problems. The matrixdist R package aims to provide researchers and practitioners a wide set of tools for analysing and modelling complex data using matrix distributions.