An informative prior probability distribution of the gompertz parameters for bayesian approaches in paleodemography

Objectives In paleodemography, the Bayesian approach has been suggested to provide an effective means by which mortality profiles of past populations can be adequately estimated, and thus avoid problems of “age‐mimicry” inherent in conventional approaches. In this study, we propose an application of the Gompertz model using an “informative” prior probability distribution by revising a recent example of the Bayesian approach based on an “uninformative” distribution. Methods Life‐table data of 134 human populations including those of contemporary hunter‐gatherers were used to determine the Gompertz parameters of each population. In each population, we used both raw life‐table data and the Gompertz parameters to calculate some demographic values such as the mean life‐span, to confirm representativeness of the model. Then, the correlation between the two Gompertz parameters (the Strehler–Mildvan correlation) was re‐established. We incorporated the correlation into the Bayesian approach as an “informative” prior probability distribution, and tested its effectiveness using simulated data. Results Our analyses showed that the mean life‐span (≥ age 15) and the proportion of living persons aging over 45 were well‐reproduced by the Gompertz model. The simulation showed that using the correlation as an informative prior provides a narrower estimation range in the Bayesian approach than does the uninformative prior. Conclusions The Gompertz model can be assumed to accurately estimate the mean life‐span and/or the proportion of old people in a population. We suggest that the Strehler–Mildvan correlation can be used as a useful constraint in demographic reconstructions of past human populations. Am J Phys Anthropol 159:523–533, 2016. © 2015 Wiley Periodicals, Inc.