Comparing loss functions and interval estimates for survival data

Starrlight Augustine*, Konstadia Lika, Sebastiaan A.L.M. Kooijman

*Corresponding author for this work

Research output: Contribution to JournalArticleAcademicpeer-review

Abstract

We compare parameter point and interval estimates based on the symmetric bounded loss function, as used in the Add-my-Pet collection on animal energetics, with the maximum likelihood method for number of surviving individuals as function of time. The aging module of Dynamic Energy Budget theory is used to generate Monte Carlo data sets. The simulations show that estimates based on the symmetric loss function give almost the same results in terms of point as well as interval estimates, compared to maximum likelihood estimation, while this loss function avoids the need to model the stochastic component of data sets. For most data types on energetics, we don't have such stochastic models, so maximum likelihood methods cannot be used. Our findings support the view that model plasticity dominates interval estimates, rather than the detailed structure of the stochastic component.

Original languageEnglish
Article number109077
Pages (from-to)1-4
Number of pages4
JournalEcological Modelling
Volume430
Early online date27 May 2020
DOIs
Publication statusPublished - 15 Aug 2020

Keywords

  • Add-my-Pet
  • Aging
  • Dynamic energy budget theory
  • Maximum likelihood
  • Profile-based interval estimates
  • Survival data
  • Symmetric bounded loss function

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