. We propose a general class of Bayesian generalized additive models for zero-inflated and overdispersed count data within … smoothness priors. We develop Bayesian inference based on Markov chain Monte Carlo simulation techniques where suitable proposal …

models. Recently, a Bayesian version for P-splines has been developed on the basis of Markov chain Monte Carlo simulation … techniques for inference. In this work we adopt and generalize the concept of Bayesian contour probabilities to additive models … called Bayesian p-value) for which a particular parameter vector of interest lies within the corresponding highest posterior …

fields. Due to the high complexity of the models statistical inference is fully Bayesian and based on highly efficient Markov …

In this paper, we propose a unified Bayesian approach for multivariate structured additive distributional regression …