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Performance of Some Ridge Regression Estimators for the Multinomial Logit Model
Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics. (Statistik)
Jönköping University, Jönköping International Business School, JIBS, Economics, Finance and Statistics. (Statistik)
Department of Mathematics and Statistics, Florida International University, Miami, Florida, USA.
2014 (English)In: Communications in Statistics - Theory and Methods, ISSN 0361-0926, E-ISSN 1532-415XArticle in journal (Refereed) Epub ahead of print
Abstract [en]

This paper considers several estimators for estimating the ridge parameter  for multinomial logit model based on the work of Khalaf and Shukur (2005), Alkhamisi, Khalaf and Shukur (2006) and  Muniz, Kibria and Shukur (2012). The mean square error (MSE) is considered as the performance criterion. A simulation study has been conducted to compare the performance of the estimators.  Based on the simulation study we found that, increasing the correlation between the independent variables and the number of regressors has negative effect on the MSE. However, when the sample size increases the MSE decreases even when the correlation between the independent variables is large. Based on the minimum MSE criterion some useful estimators for estimating the ridge parameter k are recommended for the practitioners.

Place, publisher, year, edition, pages
2014.
Keyword [en]
Estimation, LSE, MSE, Multicollinearity, Multinomial Logit, Ridge Regression, Simulation, AMS
National Category
Social Sciences
Identifiers
URN: urn:nbn:se:hj:diva-20958DOI: 10.1080/03610926.2013.784996Local ID: IHHEFSISOAI: oai:DiVA.org:hj-20958DiVA: diva2:616823
Available from: 2013-04-18 Created: 2013-04-18 Last updated: 2015-08-07

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Månsson, KristoferShukur, Ghazi
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