Mortality and aging in a heterogeneous population: a stochastic process model with observed and unobserved variables.

Journal Article

Various multivariate stochastic process models have been developed to represent human physiological aging and mortality. These efforts are extended by considering the effects of observed and unobserved state variables on the age trajectory of physiological parameters. This is done by deriving the Kolmogorov-Fokker-Planck equations describing the distribution of the unobserved state variables conditional on the history of the observed state variables. Given some assumptions, it is proved that the distribution is Gaussian. Strategies for estimating the parameters of the distribution are suggested based on an extension of the theory of Kalman filters to include systematic mortality selection. Various empirical applications of the model to studies of human aging and mortality as well as to other types of "failure" processes in heterogeneous populations are discussed.

Full Text

Duke Authors

Cited Authors

  • Yashin, AI; Manton, KG; Vaupel, JW

Published Date

  • April 1985

Published In

Volume / Issue

  • 27 / 2

Start / End Page

  • 154 - 175

PubMed ID

  • 4023952

International Standard Serial Number (ISSN)

  • 0040-5809

Language

  • eng

Conference Location

  • United States