Possibilistic Logistic Regression : in Fuzzy Environment

Language: English

Published by LAP LAMBERT Academic Publishing, 2012

365926363X / 9783659263637

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nach der Bestellung gedruckt Neuware - Printed after ordering - Parameter estimation for logistic regression is usually based on maximizing the likelihood function. For large well-balanced datasets ML estimation is a satisfactory approach. Unfortunately, ML may fail completely or at least produce poor results in terms of estimated probabilities and confidence intervals of parameters, specially for small datasets. This study extends logistic regression model to fuzzy logistic regression model by suggesting a new approach based on fuzzy concepts to estimate the model parameters. This study produces three proposed mathematical models with different objective functions. The first is formulated as a bi-objective programming model. The second is formulated using a goal programming approach, while the third is a mathematical programming model which minimizes the total spread of the estimated probabilities of the logistic model. The proposed models are evaluated and their results are compared to ML results through a Monte Carlo simulation study. The results are analyzed and summarized to conclude the following: The proposed models outperform ML approach for small size data sets with respect to the similarity measure as goodness of fit index.

Seller Inventory # 9783659263637

Title
Possibilistic Logistic Regression : in Fuzzy Environment
Author
Hesham A. Abdalla
Publisher
LAP LAMBERT Academic Publishing
Publication year
2012
Condition
Neu
Binding
Taschenbuch
Language
English
ISBN 10
365926363X
ISBN 13
9783659263637
Item weight
203 grams
Dimensions
220x150x9 mm

AHA-BUCH GmbH

Einbeck, Germany

5-star seller

AbeBooks seller since August 14, 2006

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