A Calibration Function Built From Change Points: a Review
In this work are compared using simulation methods for estimating Breslow, Efron and exact in Cox regression, to find the estimate of the model parameters, obtaining confidence intervals by resampling the Bootstrap, Jackknife and traditional asymptotic. Are generated samples of times using the inverse...
- Autores:
-
Ramírez Montoya, Javier
Regino, Ever
Guerrero, Stalyn
- Tipo de recurso:
- Fecha de publicación:
- 2017
- Institución:
- Universidad Santo Tomás
- Repositorio:
- Repositorio Institucional USTA
- Idioma:
- spa
- OAI Identifier:
- oai:repository.usta.edu.co:11634/6500
- Palabra clave:
- Regression of Cox; Bootstrap; Jackknife.
Calibración; modelos mixtos; punto de cambio
- Rights
- License
- Copyright (c) 2017 Comunicaciones en Estadística
| Summary: | In this work are compared using simulation methods for estimating Breslow, Efron and exact in Cox regression, to find the estimate of the model parameters, obtaining confidence intervals by resampling the Bootstrap, Jackknife and traditional asymptotic. Are generated samples of times using the inverse of the transformation, for models of exponential regression and Weibull. It illustrates the results of the amplitudes of the confidence intervals taking as a reference the regression estimate parametric. Showing the efficiency of these intervals. |
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