A New Robust Approach for Multinomial Logistic Regression With Complex Design Model

dc.contributor.author	Castilla, Elena
dc.contributor.author	Chocano, Pedro J.
dc.date.accessioned	2023-12-18T14:30:45Z
dc.date.available	2023-12-18T14:30:45Z
dc.date.issued	2022-06-29
dc.identifier.citation	E. Castilla and P. J. Chocano, "A New Robust Approach for Multinomial Logistic Regression With Complex Design Model," in IEEE Transactions on Information Theory, vol. 68, no. 11, pp. 7379-7395, Nov. 2022, doi: 10.1109/TIT.2022.3187063.	es
dc.identifier.issn	1557-9654
dc.identifier.uri	https://hdl.handle.net/10115/27412
dc.description.abstract	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.	es
dc.language.iso	eng	es
dc.publisher	IEEE	es
dc.subject	Divergence measures	es
dc.subject	Influence function	es
dc.subject	Multinomial logistic regression model	es
dc.subject	Robustness	es
dc.subject	Wald-type tests	es
dc.title	A New Robust Approach for Multinomial Logistic Regression With Complex Design Model	es
dc.type	info:eu-repo/semantics/article	es
dc.identifier.doi	10.1109/TIT.2022.3187063	es
dc.rights.accessRights	info:eu-repo/semantics/embargoedAccess	es