Antisampling for estimation: An Overview
Rowe, Neil C.
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We survey a new way to get quick estimates of the values of simple statistics (like count, mean, standard deviation, maximum, median, and mode frequency) on a large data set. This approach is a comprehensive attempt (apparently the first) to estimate statistics without any sampling. Our "antisampling" techniques have analogies to those of sampling, and exhibit similar estimation accuracy, but can be done much faster than sampling with large computer databases. Antisampling exploits computer science ideas from database theory and expert systems, building an auxiliary structure called a "database abstract". We make detailed comparisions to several different kinds of sampling.
The views and conclusions contained in this document are those of the author and should not be interpreted as representative of the official policies of DARPA, the Navy, or the U.S. Government.IEEE Transactions on Software Engineering, SE-11, no. 10 (October 1985), 1081-1091. The equations were redrawn in 2008.
RightsThis publication is a work of the U.S. Government as defined in Title 17, United States Code, Section 101. Copyright protection is not available for this work in the United States.
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