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Application Of An Evolutionary Algorithm To Multivariate Optimal Allocation In Stratified Sample Designs.pdf

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Preview of Application of an Evolutionary Algorithm to Multivariate Optimal Allocation in Stratified Sample Designs
🔗 Source: irs.gov
📊 Size: 58 KB
👤 Author: jnwill00
⬇️ Downloads: 346

Summary

An evolutionary algorithm is applied to the problem of multivariate optimal allocation in stratified sample designs, which is used to increase the precision of estimates for the whole population and to obtain more precise estimates for interesting domains. The algorithm adopts biological evolution as a model for computation and uses a "fitness" function to evaluate the quality of each solution. The process involves generating a population of candidate solutions, evaluating their fitness, selecting pairs to reproduce, and applying crossover and mutation operators to produce new solutions. The algorithm continues until a convergence criterion is reached or a maximum number of generations is reached, and elitism is used to ensure that the best solution is not lost. The goal is to find the optimal allocation of sample units to strata, which can be done simultaneously with finding the optimal strata boundaries, potentially producing better results than standard methods.

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An evolutionary algorithm is applied to the problem of multivariate optimal allocation in stratified sample designs, which is used to increase the precision of...

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  • File Format: PDF
  • File Size: 58 KB
  • Pages: 7
  • Language: EN
  • Author: jnwill00
  • Total Downloads: 346
  • Last Updated: 2 hours ago

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Application guideApplication tutorialEvolutionary guideEvolutionary tutorialAlgorithm guideAlgorithm tutorialMultivariate guideMultivariate tutorialOptimal guideOptimal tutorialAllocation guideAllocation tutorialStratified guideStratified tutorialSample guideSample tutorialDesigns guideDesigns tutorial

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