Abstract
In stratified sampling with k different variables and H strata it is often of interest to minimize the survey cost with respect to variance restrictions on each of the k variables. This problem has previously been solved using compromise solutions or using a linear approximation to this nonlinear problem. In this paper a nonlinear optimization routine is tested on this problem. The formulation of the problem in its original form proved problematic. For the test cases run, the transformation th = l/nh, where nh is the number of samples in stratum h, performed best when k and H are less than 7. As the number of strata and variables increase, the transformation th = nh 2 performs better. In addition, simple modifications to the routine used can improve the convergence.
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Recommended Citation
Williams, M. and Schreuder, H. T.
(1993).
"A COMPARISON OF ALGORITHMS FOR SELECTING AN OPTIMUM SAMPLE FROM H STRATA USING k VARIABLES,"
Conference on Applied Statistics in Agriculture.
https://doi.org/10.4148/2475-7772.1383
A COMPARISON OF ALGORITHMS FOR SELECTING AN OPTIMUM SAMPLE FROM H STRATA USING k VARIABLES
In stratified sampling with k different variables and H strata it is often of interest to minimize the survey cost with respect to variance restrictions on each of the k variables. This problem has previously been solved using compromise solutions or using a linear approximation to this nonlinear problem. In this paper a nonlinear optimization routine is tested on this problem. The formulation of the problem in its original form proved problematic. For the test cases run, the transformation th = l/nh, where nh is the number of samples in stratum h, performed best when k and H are less than 7. As the number of strata and variables increase, the transformation th = nh 2 performs better. In addition, simple modifications to the routine used can improve the convergence.
