Robust estimation based on grouped-adjusted data in linear regression models
β Scribed by Kazumitsu Nawata
- Publisher
- Elsevier Science
- Year
- 1990
- Tongue
- English
- Weight
- 826 KB
- Volume
- 43
- Category
- Article
- ISSN
- 0304-4076
No coin nor oath required. For personal study only.
π SIMILAR VOLUMES
## Abstract We propose a robust Cox regression model with outliers. The model is fit by trimming the smallest contributions to the partial likelihood. To do so, we implement a Metropolisβtype maximization routine, and show its convergence to a global optimum. We discuss global robustness properties
Liang and Zeger introduced a class of estimating equations that gives consistent estimates of regression parameters and of their variances in the class of generalized linear models for longitudinal data. When the response variable in such models is subject to overdispersion, the oerdispersion parame