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 |
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