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Дата изменения: Wed Aug 9 20:40:47 2000
Дата индексирования: Mon Oct 1 22:47:11 2012
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Stratified sampling Parameterization of multi-particle phase Adaptive Monte Carlo integration Importance sampling Contents

Stratified sampling

The idea of stratified sampling method is to divide a volume of integration into a large number of sub-volumes and calculate integrals separately in each sub-volume. This method produces a smaller uncertainty comparing with the direct Monte Carlo method because here the uncertainty is caused only by a function variance in the sub-volumes, while the integrand variation from one sub-volume to another does not contribute to the uncertainty.

The stratified sampling method is used to estimate the integral for any VEGAS iteration. The larger number Ncall is chosen, the smaller size of sub-volume becomes available and, consequently, the more successfully the stratified sampling works.