Generalized Extreme Value Additive Model Analysis Via Mean Field Variational Bayes

Generalized Extreme Value Additive Model Analysis Via Mean Field Variational Bayes

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Article ID: iaor2012776
Volume: 53
Issue: 3
Start Page Number: 305
End Page Number: 330
Publication Date: Sep 2011
Journal: Australian & New Zealand Journal of Statistics
Authors: , ,
Keywords: Australia, Bayesian analysis, Bayesian modelling
Abstract:

We develop Mean Field Variational Bayes methodology for fast approximate inference in Bayesian Generalized Extreme Value additive model analysis. Such models are useful for flexibly assessing the impact of continuous predictor variables on sample extremes. The new methodology allows large Bayesian models to be fitted and assessed without the significant computing costs of Markov Chain Monte Carlo methods. We illustrate our new methodology with maximum rainfall data from the Sydney, Australia, hinterland. Comparisons are made between the Mean Field Variational Bayes and Markov Chain Monte Carlo approaches.

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