-1414.Important choices for efficient and accurate evaluation of marginal likelihoods by means of Monte Carlo simulation methods are … importance sampling or the independence chain Metropolis-Hastings algorithm for posterior analysis. A comparative analysis is … presented of possible advantages and limitations of different simulation techniques; of possible choices of candidate …

Strategic choices for efficient and accurate evaluation of marginal likelihoods by means of Monte Carlo simulation … possible advantages and limitations of different simulation techniques; of possible choices of candidate distributions and … flexible estimation strategy is demonstrated where the complete posterior distribution is explored. Given an appropriately yet …

varying size. Based on the new modelling framework and the associated estimation technique, we find remarkable changes in the …

evaluating the likelihood, two of the methods rely on Monte Carlo integration with importance sampling techniques. The third …

Adaptive Polar Sampling (APS) is proposed as a Markov chain Monte Carlomethod for Bayesian analysis of models with ill …

used in importance sampling for model estimation, model selection and model combination. The procedure is fully automatic …This paper proposes an up-to-date review of estimation strategies available for the Bayesian inference of GARCH …

A class of adaptive sampling methods is introduced for efficient posterior and predictive simulation. The proposed … target and mixture is minimized. We label this approach Mixture of t by Importance Sampling and Expectation Maximization … a sequential manner, so that the candidate distribution for posterior simulation is cleverly updated when new data …