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...
- Autores:
-
Sánchez, Alfonso
Solanilla, Leonardo
Clavijo, Jairo
Zambrano, Alex
- Tipo de recurso:
- Fecha de publicación:
- 2010
- Institución:
- Universidad Santo Tomás
- Repositorio:
- Repositorio Institucional USTA
- 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
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. |
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