IDEAS home Printed from https://ideas.repec.org/a/cup/anacsi/v20y2026i2p217-251_2.html

matrixdist: an R package for statistical analysis of matrix distributions

Author

Listed:
  • Bladt, Martin
  • Mueller, Alaric
  • Yslas, Jorge

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-maximization 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 analyzing and modeling complex data using matrix distributions.

Suggested Citation

  • Bladt, Martin & Mueller, Alaric & Yslas, Jorge, 2026. "matrixdist: an R package for statistical analysis of matrix distributions," Annals of Actuarial Science, Cambridge University Press, vol. 20(2), pages 217-251, July.
  • Handle: RePEc:cup:anacsi:v:20:y:2026:i:2:p:217-251_2
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S1748499525100134/type/journal_article
    File Function: link to article abstract page
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:cup:anacsi:v:20:y:2026:i:2:p:217-251_2. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Kirk Stebbing (email available below). General contact details of provider: https://www.cambridge.org/aas .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.