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Een toepassing van “importance sampling”
Author(s) -
KLEIJNEN J. P. C.
Publication year - 1968
Publication title -
statistica neerlandica
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.52
H-Index - 39
eISSN - 1467-9574
pISSN - 0039-0402
DOI - 10.1111/j.1467-9574.1960.tb00631.x
Subject(s) - monte carlo method , rejection sampling , mathematics , computation , sample size determination , sampling (signal processing) , statistics , exponential function , slice sampling , monte carlo integration , sample (material) , importance sampling , hybrid monte carlo , algorithm , mathematical optimization , computer science , markov chain monte carlo , mathematical analysis , physics , filter (signal processing) , computer vision , thermodynamics
Summary This paper describes an experiment with “importance sampling”, to show how much reduction of the computation time and sample size can be achieved in comparison with the usual Monte Carlo method. A comparison is made between each of the three methods of “importance sampling” and the usual Monte Carlo method by the determination of the expression Of the three methods A, B and C the first one uses the shifted exponential distribution, the second one uses the gamma distribution, and the third one uses the exponential distribution with modified parameter. These three methods have all smaller variances, ranges and sample sizes than the usual Monte Carlo method. Their order of preference is A, B, C. With respect to computing time only the method A is significantly better. So only the method A is an improvement in respect of both the sample size and the computing time.