Abstract
In 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.
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Guo, H., Hou, WC., Yan, F., Zhu, Q. (2005). A Metropolis Sampling Method for Drawing Representative Samples from Large Databases. In: Zhou, L., Ooi, B.C., Meng, X. (eds) Database Systems for Advanced Applications. DASFAA 2005. Lecture Notes in Computer Science, vol 3453. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11408079_21
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DOI: https://doi.org/10.1007/11408079_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-25334-1
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