Generalised Extreme Value geoadditive model analysis via variational Bayes

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Conference Proceeding
Procedia Environmental Sciences, 2011, pp. 8 - 13
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We devise a variationalBayes algorithm for fast approximate inference in Bayesian GeneralizedExtremeValue additive modelanalysis. 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 Monte Carlo methods
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