Resource title

Bayesian Model Discrimination and Bayes Factors for Normal Linear State Space Models

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Resource description

It is suggested to discriminate between different state space models for a given time series by means of a Bayesian approach which chooses the model that minimizes the expected loss. Practical implementation of this procedures requires a fully Bayesian analysis for both the state vector and the unknown hyperparameters which is carried out by Markov chain Monte Carlo methods. Application to some non-standard situations such as testing hypotheses on the boundary of the parameter space, discriminating non-nested models and discrimination of more than two models is discussed in detail. (author's abstract) ; Series: Forschungsberichte / Institut für Statistik

Resource author

Sylvia Frühwirth-Schnatter

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en

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application/pdf

Resource resource URL

http://epub.wu.ac.at/108/1/document.pdf

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