Research Articles
Liu-Type logistic estimator under Stochastic Linear Restrictions
Authors:
Nagarajah Varathan ,
University of Peradeniya, Peradeniya, LK
About Nagarajah
Postgraduate Institute of Science
Department of Mathematics and Statistics, University of Jaffna, Jaffna
Pushpakanthie Wijekoon
University of Peradeniya, Peradeniya, LK
About Pushpakanthie
Department of Statistics and Computer Science
Abstract
To conquer the multicollinearity problem in logistic regression, many alternative estimators have been proposed in the literature when some linear restrictions on the parameter space are available in addition to the sample model. In this paper, we propose a new two parameter Liu-type estimator called Stochastic Restricted Liu-Type Logistic Estimator (SRLTLE) by combining Liu-type estimator with the logistic model in the presence of stochastic linear restrictions. Further, a Monte Carlo simulation study is done to compare the performance of the proposed estimator with some existing estimators in the scalar mean squared error (SMSE) sense, and a numerical example is given to illustrate the theoretical results.
How to Cite:
Varathan, N., & Wijekoon, P. (2018). Liu-Type logistic estimator under Stochastic Linear Restrictions. Ceylon Journal of Science, 47(1), 21–34. DOI: http://doi.org/10.4038/cjs.v47i1.7483
Published on
27 Mar 2018.
Peer Reviewed
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