This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.
Abstract Details
Activity Number:
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680
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Type:
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Contributed
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Date/Time:
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Thursday, August 5, 2010 : 10:30 AM to 12:20 PM
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Sponsor:
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Section on Statistical Computing
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Abstract - #307591 |
Title:
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A Stochastic Search Approach to Solving the Cell Suppression Problem for Three-Dimensional Hierarchical Tables
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Author(s):
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Matt Fetter*+
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Companies:
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National Agricultural Statistics Service
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Address:
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1400 Independence Avenue, SW, Washington, DC, 20250,
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Keywords:
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stochastic search ;
disclosure risk ;
cell suppression
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Abstract:
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Cell suppression is one method that is commonly used to reduce disclosure risk when data are published in hierarchical tables. A form of optimality is achieved for 2-dimensional tables by formulating the cell suppression problem as a minimum cost flow problem. There are issues with this approach in general, and for its application to 3-dimensional tables in particular. First, cell suppression is fundamentally an integer programming problem with a non-smooth cost function. Secondly, the minimum cost flow approach is not directly applicable to 3-dimensional tables. A stochastic search approach is presented that is guaranteed to generate closed paths in 3-dimensional tables. Although no claim of optimality can be made, this method is capable of finding good solutions using significantly fewer iterations than a similarly constrained blind random search.
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