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- W1546706057 abstract "AbstractIn this paper, a sampling method based on the Metropolis algorithm is proposed. It is able to draw samples that have the same distribution as the underlying probability distribution. It is a simple, efficient, and powerful method suitable for all distributions. We have performed experiments to examine the qualities of the samples by comparing their statistical properties with the underlying population. The experimental results show that the samples selected by our method are bona fide representative.KeywordsRandom Number GeneratorMonte Carlo StepMetropolis AlgorithmTurnout RateTrial ObjectThese keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves." @default.
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- W1546706057 date "2005-01-01" @default.
- W1546706057 modified "2023-09-26" @default.
- W1546706057 title "A Metropolis Sampling Method for Drawing Representative Samples from Large Databases" @default.
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- W1546706057 doi "https://doi.org/10.1007/11408079_21" @default.
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