This is the program for the 2010 Joint Statistical Meetings in Vancouver, British Columbia.

Abstract Details

Activity Number: 243
Type: Contributed
Date/Time: Monday, August 2, 2010 : 2:00 PM to 3:50 PM
Sponsor: Section on Government Statistics
Abstract - #307471
Title: Stratification of a Sampling Frame with Auxiliary Data Into Piecewise Linear Segments by Means of a Genetic Algorithm
Author(s): Joseph James Barth*+ and Yang Cheng
Companies: U.S. Census Bureau and U.S. Census Bureau
Address: 8510 16th St. #105, Silver Spring, MD, 20910,
Keywords: Piecewise linear fit ; genetic algorithm ; survey design ; stratification

Regression-based estimators are used for several surveys conducted by the Governments Division of the U.S. Census Bureau. One assumption of this style of estimator is that the auxiliary variable has a roughly linear relationship with the estimated variables. We propose a genetic algorithm to stratify the frame population with auxiliary data in such a way that the data fit a linear relationship in each stratum. To do this, we make the assumption that we know the maximum number of partitions for a piecewise linear fit. In particular, we consider the case of dividing an interval into at most three piecewise linear segments, with concepts that generalize naturally to any arbitrary maximum. We first explore two families of piecewise linear fits with different levels of perturbation. Finally, we apply this method to real Governments Division data.

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