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Performance of Some Ridge Regression Estimators for the Multinomial Logit Model
Jönköping University.
Linnaeus University, School of Business and Economics, Department of Economics and Statistics. Jönköping University. (LNUC)ORCID iD: 0000-0002-3416-5896
Florida International University, USA.
2017 (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
Taylor & Francis, 2017.
National Category
Probability Theory and Statistics
Research subject
Statistics/Econometrics
Identifiers
URN: urn:nbn:se:lnu:diva-25351DOI: 10.1080/03610926.2013.784996OAI: oai:DiVA.org:lnu-25351DiVA: diva2:616822
Available from: 2013-04-18 Created: 2013-04-18 Last updated: 2017-04-10

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CiteExportLink to record
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  • apa
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