Free Content Review of Methods for Fitting Time-Series Models with Process and Observation Error and Likelihood Calculations for Nonlinear, Non-gaussian State-Space Models

 Download
(PDF 154.4kb)
 
Download Article:

Abstract:

A key challenge for analyzing fisheries time-series data has been to incorporate sources of uncertainty such as process error, observation error, and model-structure uncertainty. Recent years have seen promising advances in methods for handling the first two together in a state-space framework, but likelihood calculations for state-space models require high-dimensional integrals, which make their use computationally challenging. The first section of this paper reviews model-fitting methods that use a state-space model structure, including errors-in-variables methods, Bayesian methods that do and do not use the state-space likelihood, and the possibility of classical likelihood analysis with nonlinear, non-Gaussian state-space models. It also discusses the relationship between true likelihood calculations and errors-in-variables likelihoods, as well as the role of Monte Carlo methods in implementing Bayesian and/or state-space model analyses. The second section introduces a numerical method for calculating state-space likelihoods without Monte Carlo methods and gives examples in a classical maximum-likelihood framework. The method is applicable when the dimension of the state space at each time step is low. Although recent advances in model-fitting and analysis methods are promising, inferences from noisy data and complex processes will continue to be variable and uncertain.

Document Type: Research Article

Publication date: March 1, 2002

More about this publication?
  • The Bulletin of Marine Science is dedicated to the dissemination of high quality research from the world's oceans. All aspects of marine science are treated by the Bulletin of Marine Science, including papers in marine biology, biological oceanography, fisheries, marine affairs, applied marine physics, marine geology and geophysics, marine and atmospheric chemistry, and meteorology and physical oceanography.
  • Editorial Board
  • Information for Authors
  • Subscribe to this Title
  • Terms & Conditions
  • ingentaconnect is not responsible for the content or availability of external websites
Related content

Tools

Favourites

Share Content

Access Key

Free Content
Free content
New Content
New content
Open Access Content
Open access content
Subscribed Content
Subscribed content
Free Trial Content
Free trial content
Cookie Policy
X
Cookie Policy
ingentaconnect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more