A New Robust Approach for Multinomial Logistic Regression With Complex Design Model
Robust estimators and Wald-type tests are developed for the multinomial logistic regression based on φ-divergence measures. We compute the influence function of the proposed estimators and tests and discuss some consequences. Their robustness is illustrated by an extensive simulation study and two r...
| Autores: | , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2022 |
| País: | España |
| Institución: | Universidad Rey Juan Carlos |
| Repositorio: | BURJC-Digital. Repositorio Institucional de la Universidad Rey Juan Carlos |
| OAI Identifier: | oai:burjcdigital.urjc.es:10115/27412 |
| Acceso en línea: | https://hdl.handle.net/10115/27412 |
| Access Level: | acceso embargado |
| Palabra clave: | Divergence measures Influence function Multinomial logistic regression model Robustness Wald-type tests |
| Sumario: | Robust estimators and Wald-type tests are developed for the multinomial logistic regression based on φ-divergence measures. We compute the influence function of the proposed estimators and tests and discuss some consequences. Their robustness is illustrated by an extensive simulation study and two real examples. |
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