Kahn, H.; Marshall, A. W. Methods of reducing sample size in Monte Carlo computations. (English) Zbl 1414.90373 Oper. Res. 1, No. 5, 263-278 (1953). Summary: This paper deals with the problem of increasing the efficiency of Monte Carlo calculations. The methods of doing so permit one to reduce the sample size required to produce estimates of a fixed level of accuracy or, alternatively, to increase the accuracy of the estimates for a fixed cost of computation. Few theorems are known with regard to optimal sampling schemes, but several helpful ideas of very general applicability are available for use in designing Monte Carlo sampling schemes. Three of these ideas are discussed and illustrated in simple cases. These ideas are (1) correlation of samples, (2) importance sampling, and (3) statistical estimation. Cited in 35 Documents MSC: 90C90 Applications of mathematical programming 65K05 Numerical mathematical programming methods 65C05 Monte Carlo methods 62D05 Sampling theory, sample surveys 62P20 Applications of statistics to economics PDFBibTeX XMLCite \textit{H. Kahn} and \textit{A. W. Marshall}, Oper. Res. 1, No. 5, 263--278 (1953; Zbl 1414.90373) Full Text: DOI