Density-dependent state-space model for population-abundance data with unequal time intervals.

ABSTRACT: The Gompertz state-space (GSS) model is a stochastic model for analyzing time-series observations of population abundances. The GSS model combines density dependence, environmental process noise, and observation error toward estimating quantities of interest in biological monitoring and population viability analysis. However, existing methods for estimating the model parameters apply only to population data with equal time intervals between observations. In the present paper, we extend the GSS model to data with unequal time intervals, by embedding it within a state-space version of the Ornstein-Uhlenbeck process, a continuous-time model of an equilibrating stochastic system. Maximum likelihood and restricted maximum likelihood calculations for the Ornstein-Uhlenbeck state-space model invo

SUBMITTER: Dennis B 

PROVIDER: S-EPMC4267252 | biostudies-literature | 2014 Aug

REPOSITORIES: biostudies-literature