Performance of some ridge regression estimators for the multinomial logit model

Kristofer Månsson, Ghazi Shukur and B. M. Golam Kibria

Communications in Statistics - Theory and Methods, 2018, vol. 47, issue 12, 2795-2804

Abstract: This article considers several estimators for estimating the ridge parameter k for multinomial logit model based on the work of Khalaf and Shukur (2005), Alkhamisi et al. (2006), and Muniz et al. (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.

Date: 2018
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DOI: 10.1080/03610926.2013.784996

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