A Bayesian approach to model selection in stochastic coefficient regression models and structural time series models

DOI10.1016/0304-4076(95)01781-XzbMath0877.62105MaRDI QIDQ1362024

Thomas S. Shively, Robert Kohn

Publication date: 15 December 1997

Published in: Journal of Econometrics (Search for Journal in Brave)

zbMATH Keywords

Kalman filterstate space modelposterior probabilityBayesian model selection procedure

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Inference from stochastic processes and prediction (62M20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Bayesian inference (62F15)

Related Items

Estimating marginal likelihoods for mixture and Markov switching models using bridge sampling techniques*, Semiparametric Bayesian inference in smooth coefficient models, Stochastic model specification search for Gaussian and partial non-Gaussian state space models, Dynamic efficiency in the east European emerging markets, BAYESIAN DYNAMIC VARIABLE SELECTION IN HIGH DIMENSIONS, Testing for integration using evolving trend and seasonals models: A Bayesian approach.

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Bayesian and non-Bayesian methods for combining models and forecasts with applications to forecasting international growth rates
• Bayesian forecasting and dynamic models
• Inference from iterative simulation using multiple sequences
• FILTERING AND SMOOTHING IN STATE SPACE MODELS WITH PARTIALLY DIFFUSE INITIAL CONDITIONS
• Testing for deterministic trend and seasonal components in time series models
• AN EXACT TEST FOR A STOCHASTIC COEFFICIENT IN A TIME SERIES REGRESSION MODEL
• Two Methods for Examining the Stability of Regression Coefficients
• An Exact Test for the Presence of Random Walk Coefficients in a Linear Regression Model