Monte Carlo methods. Vol. 1: basics
Monte Carlo methods. Vol. 1: basics
Statistical estimators for aggregate relational algebra queries
ACM Transactions on Database Systems (TODS)
Sequential sampling procedures for query size estimation
SIGMOD '92 Proceedings of the 1992 ACM SIGMOD international conference on Management of data
Query size estimation by adaptive sampling (extended abstract)
PODS '90 Proceedings of the ninth ACM SIGACT-SIGMOD-SIGART symposium on Principles of database systems
Finding generalized projected clusters in high dimensional spaces
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Density biased sampling: an improved method for data mining and clustering
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Simulation and the Monte Carlo Method
Simulation and the Monte Carlo Method
Efficient and Effective Clustering Methods for Spatial Data Mining
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
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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.