observations. A key feature of our approach is the use of the highly efficient difference estimator from the survey sampling …

Several lessons learned from a Bayesian analysis of basic economic time series models by means of the Gibbs sampling …

. The subsample is taken via the cube method, a balanced sampling design, which is defined by the property that the sample … dass dieser nicht gespeichert werden muss. Die Stichprobe wird via cube sampling, einem balanciertem Stichprobendesign …

Algorithms, Gibbs Sampling and Metropolis-Hastings Algorithm. Network and security risk management application focus is on how …

subsets are selected using an efficient Probability Proportional-to-Size (PPS) sampling scheme, where the inclusion ….We propose a simple way to adaptively choose the sample size m during the MCMC to optimize sampling efficiency for a fixed …

Monte Carlo (MC) approximation of the standard Gibbs procedure which uses sequential MC (SMC) importance sampling inside the … generic and easily implementable SMC approach known as Particle Efficient Importance Sampling (PEIS). By using SMC importance … sampling densities which are approximately fully globally adapted to the targeted density of the states, PEIS can substantially …

observations. A key feature of our approach is the use of the highly efficient difference estimator from the survey sampling …

stepping out and multivariate sampling with hyperrectangles. In the general asymmetric case, we argue that symmetrizing the … with several sampling problems. …