Estimation of an age distribution with its confidence intervals using an iterative Bayesian procedure and a bootstrap sampling approach

Abstract

An iterative Bayesian estimation procedure is used in order to explore two classes of models pertaining to the universe of preindustrial demographic mortality. One model is for attritional mortality and the other for catastrophic mortality. The estimation procedure first extracts the model which best fits the data representing the distribution of age indicators in a cemetery. Then, using the anthropological reference sample of the age indicator, a bootstrap sampling technique determines the confidence interval for the estimation. Through simulations, we show that if the cemetery belongs to the class of the models explored, i.e. if the model is true, then the result is excellent for an age/indicator correlation level of about r=0.9 © 2008 Springer Science+Business Media B.V.