Integrating multiple field measurements in a Bayesian parallel regression framework to estimate Tasmanian devil age

Understanding age structure in populations is foundational for ecological
study. Yet ascertaining the age of individuals in the wild can be
problematic. Methods typically rely on the prior determination of a
relationship between age and some morphological measurement specific to
the species or animal group under investigation. We present a novel method
to incorporate multiple measures of animal size and development to
estimate age, using Bayesian parallel regression to integrate multiple
regression relationships into predictions. We apply the method to
Tasmanian devils, a carnivorous marsupial that is threatened by a
transmissible cancer. We estimate devil age based on measures of mass,
head width, canine over-eruption and molar characteristics. This dataset
includes data required to run and test code. See published article for
full methodology.