Reversible jump methods are the most commonly used Markov chain Monte Carlo tool for exploring variable dimension statistical models. Recently, however, an alternative approach based on birth-and-death processes has been proposed by Stephens for mixtures of distributions. We show that the...

We compare Bayesian and sample theory model specification criteria. For the Bayesian criteria we use the deviance information criterion and the cumulative density of the mean squared errors of forecast. For the sample theory criterion we use the conditional Kolmogorov test. We use Markov chain...

We propose an adaptive Monte Carlo algorithm for estimating multidimensional integrals over a hyper-rectangular region. The algorithm uses iteratively the idea of separating the domain of integration into 2ssubregions. The proposed algorithm can be applied directly to estimate the integral using...

We develop a new Markov Chain Monte Carlo procedure for a time series regression model truncated by upper and lower bounds. The regression error term is assumed to follow an ARMA--GARCH process. We use a convergence diagnostics with a simultaneous test of mean and covariance stationarity and...

We develop a new Markov Chain Monte Carlo procedure for a time series regression model truncated by upper and lower bounds. The regression error term is assumed to follow an ARMA--GARCH process. We use a convergence diagnostics with a simultaneous test of mean and covariance stationarity and...

Quantum computing was so far mainly concerned with discrete problems. Recently, Novak and the author studied quantum algorithms for high dimensional integration and dealt with the question, what advantages quantum computing can bring over classical deterministic or randomized methods for this...

The stochastic method used to simulate the stationary transport in semiconductor devices is revised in terms of the numerical Monte Carlo theory. A mathematically based approach has been used to derive the basic simulation algorithms, previously devised from physical considerations. The approach...

In this paper, we consider Monte Carlo (MC) algorithms based on the use of the resolvent matrix for solving linear algebraic problems. Estimates for the speedup and efficiency of the algorithms are presented. Some numerical examples performed on cluster of workstations using MPI are given.

We apply tiling groups and height functions to tilings of regions in the plane by Wang tiles, which are squares with colored boundaries where the colors of shared edges must match. We define a set of tiles as unambiguous if it contains all tiles equivalent to the identity in its tiling group....

We consider the convergency of the basic Monte Carlo (MC) algorithms for solving the Boltzmann transport equation (BTE). It is a linear kinetic equation describing a broad class of particle transport phenomena such as electron and neutron transport, radiative transfer, medium energy electron and...