Afijación óptima de tamaños de muestra en muestreo aleatorio estratificado vía programación matemática

Somesamplingallocationproblemswhichcanbesolvedbymathematicalprogramming techniques are considered. Optimal allocation of sample sizes in Stratified Random Sampling (SI.), for example, can be regarded as a dynamic programming problem. In the multivariate case, the underlying convex–programming problem...

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Autores:
Sánchez, Alfonso
Solanilla, Leonardo
Clavijo, Jairo
Zambrano, Alex
Tipo de recurso:
Fecha de publicación:
2010
Institución:
Universidad Santo Tomás
Repositorio:
Universidad Santo Tomás
Idioma:
spa
OAI Identifier:
oai:repository.usta.edu.co:11634/39538
Acceso en línea:
https://revistas.usantotomas.edu.co/index.php/estadistica/article/view/28
http://hdl.handle.net/11634/39538
Palabra clave:
Muestreo aleatorio estratificado
Knapsack
optimización
programación matemática
Rights
License
http://purl.org/coar/access_right/c_abf2
Description
Summary:Somesamplingallocationproblemswhichcanbesolvedbymathematicalprogramming techniques are considered. Optimal allocation of sample sizes in Stratified Random Sampling (SI.), for example, can be regarded as a dynamic programming problem. In the multivariate case, the underlying convex–programming problem is stated and some solution methods are indicated. We have followed the illuminating ideas exposed in Arthanari & Dodge (1981). Finally, an example to illustrate the so-called Knapsack method is presented.