BayesX – Bayesian semiparmetric and GAM modeling

BayesX regression tools relies on Markov Chain Monte Carlo simulation techniques and restricted maximum likelihood (REML) estimation. These techniques are used in support of mixed models, semiparametric regressions and survival models with structured additive predictors (STAR). STAR models cover a number of well known model classes as special cases, including generalized additive models(GAM), generalized additive mixed models, geoadditive models, varying coefficient models, and geographically weighted regressions. These methods are useful in non-spatial and spatial settings. Covariate effects within a GAM are specifed using P-splines. Additional info can be found at: http://www.stat.uni-muenchen.de/~bayesx/bayesx.html

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