Assessing movement patterns using Bayesian state space models on Lake Winnipeg walleye

Morphological and trophic differentiation of growth morphotypes of walleye (Sander vitreus) from Lake Winnipeg, Canada

Ecologically related polymorphisms occur in many northern freshwater fish populations and are distinguished by alternate phenotypes consistently associated with differential use of habitats or resources. We tested for polymorphism in walleye (Sander vitreus (Mitchill, 1818)) in the south basin of Lake Winnipeg, where evidence suggests that ‘‘dwarf’’ and ‘‘normal’’ growth forms may coexist. Morp...

Bayesian Estimation of State Space Models Using Moment Conditions∗

We consider Bayesian estimation of state space models when the measurement density is not available but estimating equations for the parameters of the measurement density are available from moment conditions. The most common applications are partial equilibrium models involving moment conditions that depend on dynamic latent variables (e.g., timevarying parameters, stochastic volatility) and dy...

Applied Bayesian Data Analysis Using State-Space Models

State-space models of individual animal movement.

Detailed observation of the movement of individual animals offers the potential to understand spatial population processes as the ultimate consequence of individual behaviour, physiological constraints and fine-scale environmental influences. However, movement data from individuals are intrinsically stochastic and often subject to severe observation error. Linking such complex data to dynamical...

Bayesian Learning in Nonlinear State-Space Models

We describe Bayesian learning in nonlinear state-space models (NSSMs). NSSMs are a general method for the probabilistic modelling of sequences and time-series. They take the form of iterated maps on continuous state-spaces, and can have either discrete or continuous valued output functions. They are generalizations of the more well known state-space models such as Hidden Markov models (HMMs), a...