Adaptive Polar Sampling (APS) is proposed as a Markov chain Monte Carlomethod for Bayesian analysis of models with ill … the location and scale.Tested on a set of canonical models that feature nearnon-identifiability, strong correlation, and …

Adaptive Polar Sampling (APS) is proposed as a Markov chain Monte Carlo method for Bayesian analysis of models with ill … is applied to update the location and scale.<BR> Tested on a set of canonical models that feature near non …

Adaptive Polar Sampling (APS) is proposed as a Markov chain Monte Carlomethod for Bayesian analysis of models with ill … the location and scale.Tested on a set of canonical models that feature nearnon-identifiability, strong correlation, and …

Highly non-elliptical posterior distributions may occur in several econometric models, in particular, when the … indirect sampling methods in these models, one has to find a good candidate density. In a recent paper - Hoogerheide, Kaashoek … sophisticated neural network simulation techniques is explored. In all examples considered in this paper - a bimodal distribution of …

. A simulation-based Bayesian procedure is introduced for predicting stable stock price ratios, defined in a cointegration … model. Using this class of models and the proposed inferential technique, we are able to connect estimation and model …. We distinguish between models with a normal and Student <I>t</I> distribution since the latter typically provides a …

implicit statistical arbitrage method. We use a simulation-based Bayesian procedure for predicting stable ratios, defined in a …

. A simulation-based Bayesian procedure is introduced for predicting stable stock price ratios, defined in a cointegration … model. Using this class of models and the proposed inferential technique, we are able to connect estimation and model …. We distinguish between models with a normal and Student t distribution since the latter typically provides a better …

Highly non-elliptical posterior distributions may occur in several econometric models, in particular, when the … indirect sampling methods in these models, one has to find a good candidate density. In a recent paper - Hoogerheide, Kaashoek … sophisticated neural network simulation techniques is explored. In all examples considered in this paper – a bimodal distribution of …

sense of having highly non-elliptical shapes. The simulation techniques are illustrated in several example models, such as a …In this paper we discuss several aspects of simulation based Bayesian econometric inference. We start at an elementary … level on basic concepts of Bayesian analysis; evaluating integrals by simulation methods is a crucial ingredient in Bayesian …