-off encountered by other sampling methods. An elaborate simulation study and an empirical application for U.S. stock returns reveal … methods. Our methodology explores the idea that only a small part of the likelihood evaluation problem requires simulation. We … refer to our new method as numerically accelerated importance sampling. The method is computationally and numerically …

simulation evidence for stochastic volatility and stochastic intensity models. For our empirical study, we analyse the …

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 …

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

-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 …