A Monte Carlo method for high dimensional integration

Authors

Yosihiko Ogata

The Institute of Statistical Mathematics

Article

Received:

DOI:
10.1007/BF01406511

Cite this article as:

Ogata, Y. Numer. Math. (1989) 55: 137. doi:10.1007/BF01406511

Summary

A new method for the numerical integration of very high dimensional functions is introduced and implemented based on the Metropolis' Monte Carlo algorithm. The logarithm of the high dimensional integral is reduced to a 1-dimensional integration of a certain statistical function with respect to a scale parameter over the range of the unit interval. The improvement in accuracy is found to be substantial comparing to the conventional crude Monte Carlo integration. Several numerical demonstrations are made, and variability of the estimates are shown.