approximation can be used as a candidate density in Importance Sampling or Metropolis Hastings methods for Bayesian inference on … model parameters and probabilities. The package provides also an extended MitISEM algorithm, 'sequential MitISEM', which … predictive likelihoods. We illustrate the MitISEM algorithm using three canonical statistical and econometric models that are …

distribution given only a kernel of the target density function. The core algorithm consists in the function AdMit which fits an … the independence chain Metropolis- Hastings algorithm are used to obtain quantities of interest for the target density … the time-consuming and difficult task of tuning a sampling algorithm. The relevance of the package is shown in two …

We develop Bayesian techniques for estimation and model comparison in a novel Generalised Stochastic Unit Root (GSTUR …

Carlo algorithm to estimate the parameters and the latent variables in an efficient one-step procedure. Via the Bayesian …

This note presents the R package bayesGARCH (Ardia, 2007) which provides functions for the Bayesian estimation of the … the tedious task of tuning a MCMC sampling algorithm. The usage of the package is shown in an empirical application to …

Bayesian techniques. A salient feature of the model is an extension of the typically postulated quadratic cost structure for …

importance sampling or the independence chain Metropolis-Hastings algorithm for posterior analysis. A comparative analysis is …

likelihood; and the censored predictive likelihood, which is used for Bayesian Model Averaging. We perform extensive experiments … posterior and traditional Bayesian Model Averaging techniques in applications of Value-at-Risk prediction in GARCH models. …

Prefetching is a simple and general method for single-chain parallelisation of the Metropolis-Hastings algorithm based … random walk Metropolis-Hastings algorithm is obtained for a special case and it is shown to decrease in the number of … processors employed. The performance of the algorithms is illustrated using a well-known macroeconomic model. Bayesian estimation …

-called peer group games being non-negative additive games on a permission tree. We provide a polynomial time algorithm for …