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Using a penalized likelihood to detect mortality deceleration

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  • Silvio C. Patricio
  • Trifon I Missov

Abstract

We suggest a novel method for detecting mortality deceleration by adding a penalty to the log-likelihood function in a gamma-Gompertz setting. This is an alternative to traditional likelihood inference and hypothesis testing. The main advantage of the proposed method is that it does not involve using a p-value, hypothesis testing, and asymptotic distributions. We evaluate the performance of our approach by comparing it with traditional likelihood inference on both simulated and real mortality data. Results have shown that our method is more accurate in detecting mortality deceleration and provides more reliable estimates of the underlying parameters. The proposed method is a significant contribution to the literature as it offers a powerful tool for analyzing mortality patterns.

Suggested Citation

  • Silvio C. Patricio & Trifon I Missov, 2023. "Using a penalized likelihood to detect mortality deceleration," PLOS ONE, Public Library of Science, vol. 18(11), pages 1-13, November.
    • Handle: RePEc:plo:pone00:0294428
    DOI: 10.1371/journal.pone.0294428
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    References listed on IDEAS

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    3. Trifon I. Missov & Maxim S. Finkelstein, 2011. "Admissible mixing distributions for a general class of mixture survival models with known asymptotics," MPIDR Working Papers WP-2011-004, Max Planck Institute for Demographic Research, Rostock, Germany.
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    6. Missov, Trifon I. & Finkelstein, Maxim, 2011. "Admissible mixing distributions for a general class of mixture survival models with known asymptotics," Theoretical Population Biology, Elsevier, vol. 80(1), pages 64-70.
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