Por favor, use este identificador para citar o enlazar este ítem:
http://cimat.repositorioinstitucional.mx/jspui/handle/1008/635| Bayesian Detection of Active Effects in Designed Experiments Modeled with GLM´S | |
| ROMAN DE LA VARA SALAZAR | |
| Acceso Abierto | |
| Atribución-NoComercial | |
| Estadística Bayesiana | |
| Unreplicated fractional factorial experiments with response modeled with Generalized linear models (GLM) are found more and more frequently in industrial applications. GLM analysis relies heavily on large sample results. This paper presents a Bayesian method for detecting the active effects in unreplicated factorial experiments analyzed by a GLM that does not require the large sample assumption. The proposed method is based on Bayesian model selection. In the examples shown, the Bayesian method produces more consistent results thaninference based on Wald’s test, and in a simulated example the usual approach brakes down while the Bayesian method identifies the significant effects correctly. The method is presented for the 2 kexperiments, but it can easily be generalized to other designs. | |
| Centro de Investigación en Matemáticas AC | |
| 27-03-2007 | |
| Reporte | |
| Inglés | |
| Investigadores | |
| ESTADÍSTICA | |
| Versión publicada | |
| publishedVersion - Versión publicada | |
| Aparece en las colecciones: | Reportes Técnicos - Probabilidad y Estadística |
Cargar archivos:
| Fichero | Tamaño | Formato | |
|---|---|---|---|
| I-07-06.pdf | 384.08 kB | Adobe PDF | Visualizar/Abrir |