Using an unified framework, we integrate the two major Monte Carlo techniques currently available: Efficient Importance Sampling (EIS) and Markov Chain Monte Carlo (MCMC). We do so for two reasons. First, the two methods complement one another. Loosely, EIS is effective for integrating...

The performance of Monte Carlo integration methods like importance-sampling or Markov-Chain Monte-Carlo procedures depends greatly on the choice of the importance- or candidate-density. Such a density must typically be "close" to the target density to yield numerically accurate results with...