I. The Statistical Model -- 1.1 Notation -- 1.2 Interpretation -- 1.3 Likelihood function -- II. Bayesian Inference: The Extended Natural-Conjugate Approach -- II.1 Two reformulations of the likelihood function -- II.2 The extended natural-conjugate prior density -- II.3 Posterior densities --...

Adaptive Polar Sampling is proposed as an algorithm where random drawings aredirectly generated from the target function (posterior) in all-but-onedirections of the parameter space. The method is based on the mixed integrationtechnique of Van Dijk, Kloek & Boender (1985) but extends this one by...

Adaptive Polar Sampling (APS) is proposed as a Markov chain Monte Carlomethod for Bayesian analysis of models with ill-behaved posteriordistributions. In order to sample efficiently from such a distribution,a location-scale transformation and a transformation to polarcoordinates are used. After...