QUT ePrints

Efficient Bayesian Estimation of Multivariate State Space Models

Strickland, Christopher M., Turner, Ian W., Denham, Robert, & Mengersen, Kerrie L. (2008) Efficient Bayesian Estimation of Multivariate State Space Models. Computational Statistics & Data Analysis, 53(12), pp. 4116-4125.

View at publisher

Abstract

A Bayesian Markov chain Monte Carlo methodology is developed for the estimation of multivariate linear Gaussian state space models. In particular, an efficient simulation smoothing algorithm is proposed that makes use of the univariate representation of the state space model. Substantial gains over existing algorithms in computational efficiency are achieved using the new simulation smoother for the analysis of high dimensional multivariate time series. The methodology is used to analyse a multivariate timeseries dataset of the Normalised Difference Vegetation Index (NDVI), which is a proxy for the level of live vegetation, for a particular grazing property located in Queensland, Australia.

Impact and interest:

6 citations in Scopus
Search Google Scholar™
6 citations in Web of Science®

Citation countsare sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

Full-text downloads:

525 since deposited on 15 Feb 2008
73 in the past twelve months

Full-text downloadsdisplays the total number of times this work’s files (e.g., a PDF) have been downloaded from QUT ePrints as well as the number of downloads in the previous 365 days. The count includes downloads for all files if a work has more than one.

ID Code: 12499
Item Type: Journal Article
Additional Information: This research was funded by an ARC linkage grant between QUT and the Department of National Resources and Water
Keywords: Multivariate, State space model, Markov chain Monte Carlo, Kalman filter, Simulation smoother, Univiarate representation, MODIS, Stochastic cycle
DOI: 10.1016/j.csda.2009.04.019
Subjects: Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > NUMERICAL AND COMPUTATIONAL MATHEMATICS (010300) > Numerical Analysis (010301)
Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > STATISTICS (010400) > Applied Statistics (010401)
Australian and New Zealand Standard Research Classification > MATHEMATICAL SCIENCES (010000) > STATISTICS (010400) > Statistics not elsewhere classified (010499)
Divisions: Past > QUT Faculties & Divisions > Faculty of Science and Technology
Copyright Owner: Copyright 2008 Elsevier
Deposited On: 15 Feb 2008
Last Modified: 04 Sep 2012 15:11

Export: EndNote | Dublin Core | BibTeX

Repository Staff Only: item control page