2005/01/01 by Wolfgang Hörmann, Hörmann, Wolfgang, Josef Leydold +1
Economics, Econometrics and Finance · Engineering · Physics and Astronomy · #Diverse Scientific and Engineering Research #Financial Risk and Volatility Modeling #Scientific Research and Discoveries
paper · doi:10.57938/2e800c62-4044-4633-8703-1184e245a677
openalex publication_date 2005/01/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/01
To evaluate the expectation of a simple function with respect to a complicated multivariate density Monte Carlo integration has become the main technique. Gibbs sampling and importance sampling are the most popular methods for this task. In this contribution we propose a new simple general purpose importance sampling procedure. In a simulation study we compare the performance of this method with the performance of Gibbs sampling and of importance sampling using a vector of independent variates. It turns out that the new procedure is much better than independent importance sampling; up to dimension five it is also better than Gibbs sampling. The simulation results indicate that for higher dimensions Gibbs sampling is superior. (author's abstract)