Starjournal Quotation Frühwirth-Schnatter, Sylvia, Wagner, Helga. 2010. Stochastic Model Specification Search for Gaussian and Partial Non-Gaussian State Space Models. Journal of Econometrics. 154 85-100.




State space models are a widely used tool in time series analysis to deal with processes which gradually change over time. Model specification however is a diffcult task as one has to decide which components to include in the model and to specify whether these are fixed or stochastic. In the Bayesian approach, model selection relies on the posterior probabilities of a model given the data. These can be determined for each model separately by using Bayes' rule, which requires estimation of the marginal likelihoods by some numerical methods. The modern approach to Bayesian model selection is to apply model space MCMC methods by sampling jointly model indicators and parameters, as e.g. in the stochastic variable selection approach (George and McCulloch, 1997), which is usually applied to model selection for regression models. In this talk we show that a stochastic model search MCMC method is feasible for Gaussian as well as non-Gaussian time series data (binary data, multinomial data, count data) that chooses appropriate components in a structural time series model and decides, if these components are deterministic or stochastic. For non-Gaussian state space models the stochastic model search MCMC methods makes use of auxiliary mixture sampling developed in Frühwirth-Schnatter and Wagner (2006) for count data and in Frühwirth- Schnatter and Frühwirth (2007) for binary and multinomial data.


Press 'enter' for creating the tag

Publication's profile

Status of publication Published
Affiliation WU
Type of publication Journal article
Journal Journal of Econometrics
Citation Index SSCI
WU Journalrating 2009 A+
Starjournal Y
Language English
Title Stochastic Model Specification Search for Gaussian and Partial Non-Gaussian State Space Models
Volume 154
Year 2010
Page from 85
Page to 100
Reviewed? Y
Open Access N


Frühwirth-Schnatter, Sylvia (Details)
Wagner, Helga
Institute for Statistics and Mathematics IN (Details)
Google Scholar: Search