IDEAS home Printed from https://ideas.repec.org/a/cup/anacsi/v19y2025i1p23-48_2.html

AffineMortality: An R package for estimation, analysis, and projection of affine mortality models

Author

Listed:
  • Ungolo, Francesco
  • Garces, Len Patrick Dominic M.
  • Sherris, Michael
  • Zhou, Yuxin

Abstract

This paper presents the AffineMortality R package which performs parameter estimation, goodness-of-fit analysis, simulation, and projection of future mortality rates for a set of affine mortality models for use in pricing and reserving. The computational routines build on the univariate Kalman Filtering approach of Koopman and Durbin ((2000). Journal of Time Series Analysis, 21(3), 281–296.) along other numerical methods to enhance the robustness of the results. This paper provides a discussion of how the package works in order to effectively estimate and project survival curves, and describes the available functions. Illustration of the package for mortality analysis of the US male data set is provided.

Suggested Citation

  • Ungolo, Francesco & Garces, Len Patrick Dominic M. & Sherris, Michael & Zhou, Yuxin, 2025. "AffineMortality: An R package for estimation, analysis, and projection of affine mortality models," Annals of Actuarial Science, Cambridge University Press, vol. 19(1), pages 23-48, March.
    • Handle: RePEc:cup:anacsi:v:19:y:2025:i:1:p:23-48_2
    as

    Download full text from publisher

    File URL: https://www.cambridge.org/core/product/identifier/S1748499524000149/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:19:y:2025:i:1:p:23-48_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.