Publication:
Antisampling for estimation: an overview

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Authors
Rowe, Neil C.
Subjects
Statistical computing, databases, query processing, production systems, estimation, constraints, inequalities, parametric optimization, sampling, expert systems, performance evaluation, variational methods.
Advisors
Date of Issue
1984-10
Date
1984-10
Publisher
Monterey, California. Naval Postgraduate School
Language
en_US
Abstract
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, by reasoning about various sets containing a population interest. Our antisampling techniques have connections to those of sampling (and have duals in many cases), but they have different advantages and disadvantages, making antisampling sometimes preferable to sampling, sometimes not. In particular, they can only be efficient when data is in a computer, and they exploit computer science ideas such as production systems and database theory. Antisampling also requires the overhead of construction of an auxiliary structure, a database abstract . Tests on sample data show similar or better performance than simple random sampling. We also discuss more complex methods of sampling and their disadvantages
Type
Technical Report
Description
Series/Report No
Department
Computer Science
Identifiers
NPS Report Number
NPS52-84-016
Sponsors
Prepared for: Chief of Naval Research
Funder
61152N; RR000-01-10 N0001484WR41001
Format
24 p. : ill. ; 28 cm.
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