On the Value of Function Evaluation Location Information in Monte Carlo Simulation
STANFORD UNIV CA DEPT OF OPERATIONS RESEARCH
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The point estimator used in naive Monte Carlo sampling weights all the computed function evaluations equally, and it does not take into account the precise locations at which the function evaluations are made. In this note, we show for one-dimensional integration problems that if the weights are suitably modified to reflect the location information present in the sample, then the convergence rate of the Monte Carlo estimator can be dramatically improved from order n-12 to order n-2, where is the number of function evaluations computed....Simulation, Monte Carlo methods, Numerical integration.
- Statistics and Probability
- Operations Research