Two new developed multinomial logistic regression approach is proposed by incorporating the concepts of fuzzy sets. The first is formulated using a goal programming approach, while the second is formulated as a multi objective programming model. These two models are based on the assumption that the parameters are fuzzy. A simulation study is used to evaluate the suggested models comparing to the classical approach. Data are generated from different multinomial logistic models The design of the simulation study considers 40 different combinations of three factors. For each combination, a comparison between the performance of the proposed approach and ML approach is presented.
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Dr Hesham A. Abdalla is Assistant Professor, Department of Statistics and Insurance, Assiut University,Assiut, Egypt. He has a Ph.D. in Operation Research-Cairo university.Dr Amany A. El-Sayed is Assistant Prof. of StatisticsFaculty of Commerce,Sohag University.Prof Ramadan Hamed is a professor of Statistics, Cairo University.
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Taschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Two new developed multinomial logistic regression approach is proposed by incorporating the concepts of fuzzy sets. The first is formulated using a goal programming approach, while the second is formulated as a multi objective programming model. These two models are based on the assumption that the parameters are fuzzy. A simulation study is used to evaluate the suggested models comparing to the classical approach. Data are generated from different multinomial logistic models The design of the simulation study considers 40 different combinations of three factors. For each combination, a comparison between the performance of the proposed approach and ML approach is presented. 124 pp. Englisch. N° de réf. du vendeur 9783659832550
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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Abdalla Hesham A.Dr Hesham A. Abdalla is Assistant Professor, Department of Statistics and Insurance, Assiut University,Assiut, Egypt. He has a Ph.D. in Operation Research-Cairo university.Dr Amany A. El-Sayed is Assistant Prof. of S. N° de réf. du vendeur 159146172
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. Neuware -Two new developed multinomial logistic regression approach is proposed by incorporating the concepts of fuzzy sets. The first is formulated using a goal programming approach, while the second is formulated as a multi objective programming model. These two models are based on the assumption that the parameters are fuzzy. A simulation study is used to evaluate the suggested models comparing to the classical approach. Data are generated from different multinomial logistic models The design of the simulation study considers 40 different combinations of three factors. For each combination, a comparison between the performance of the proposed approach and ML approach is presented.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 124 pp. Englisch. N° de réf. du vendeur 9783659832550
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Taschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Two new developed multinomial logistic regression approach is proposed by incorporating the concepts of fuzzy sets. The first is formulated using a goal programming approach, while the second is formulated as a multi objective programming model. These two models are based on the assumption that the parameters are fuzzy. A simulation study is used to evaluate the suggested models comparing to the classical approach. Data are generated from different multinomial logistic models The design of the simulation study considers 40 different combinations of three factors. For each combination, a comparison between the performance of the proposed approach and ML approach is presented. N° de réf. du vendeur 9783659832550
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Taschenbuch. Etat : Neu. Multinomial Logistic Regression with Fuzzy Parameters | Hesham A. Abdalla (u. a.) | Taschenbuch | 124 S. | Englisch | 2016 | LAP LAMBERT Academic Publishing | EAN 9783659832550 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu. N° de réf. du vendeur 103960041
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