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A New Family of BAN Estimators for Polytomous Logistic Regression Models based on ϕ- Divergence Measures

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  • A. Gupta
  • D. Kasturiratna
  • T. Nguyen
  • L. Pardo

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  • A. Gupta & D. Kasturiratna & T. Nguyen & L. Pardo, 2006. "A New Family of BAN Estimators for Polytomous Logistic Regression Models based on ϕ- Divergence Measures," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 15(2), pages 159-176, August.
    • Handle: RePEc:spr:stmapp:v:15:y:2006:i:2:p:159-176
    DOI: 10.1007/s10260-006-0008-6
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    References listed on IDEAS

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    1. Amemiya, Takeshi, 1981. "Qualitative Response Models: A Survey," Journal of Economic Literature, American Economic Association, vol. 19(4), pages 1483-1536, December.
    2. J. Engel, 1988. "Polytomous logistic regression," Statistica Neerlandica, Netherlands Society for Statistics and Operations Research, vol. 42(4), pages 233-252, December.
    3. Theil, Henri, 1969. "A Multinomial Extension of the Linear Logit Model," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 10(3), pages 251-259, October.
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    Cited by:

    1. Elena Castilla & Nirian Martín & Leandro Pardo, 2018. "Minimum phi-divergence estimators for multinomial logistic regression with complex sample design," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 102(3), pages 381-411, July.
    2. D.M. Sakate & D.N. Kashid, 2014. "Variable selection via penalized minimum φ-divergence estimation in logistic regression," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(6), pages 1233-1246, June.
    3. Pardo, L. & Pardo, M.C., 2008. "An extension of likelihood-ratio-test for testing linear hypotheses in the baseline-category logit model," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1477-1489, January.
    4. Elena Castilla & Abhik Ghosh & Nirian Martin & Leandro Pardo, 2021. "Robust semiparametric inference for polytomous logistic regression with complex survey design," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 15(3), pages 701-734, September.

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