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Modified almost unbiased Liu estimator in logistic regression

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dc.contributor.author Varathan, N.
dc.date.accessioned 2021-11-25T05:17:02Z
dc.date.accessioned 2022-06-28T06:46:05Z
dc.date.available 2021-11-25T05:17:02Z
dc.date.available 2022-06-28T06:46:05Z
dc.date.issued 2019
dc.identifier.uri http://repo.lib.jfn.ac.lk/ujrr/handle/123456789/4256
dc.description.abstract This paper focuses on introducing a new parameter estimator to the logistic regression model when the multicollinearity presents. The proposed estimator called Modified almost unbiased logistic Liu esti mator (MAULLE) is obtained by composing the Liu estimator and the almost unbiased Liu estimator. Further, conditions for the superiority of the new estimator over some existing estimators were derived with respect to mean square error (MSE) and scalar mean square error (SMSE) sense. A Monte Carlo simulation study was carried out to compare the performance of the proposed estimator with some existing estimators in the scalar mean square error sense, and a real data example was discussed to illustrate the theoretical results. en_US
dc.language.iso en en_US
dc.publisher University of Jaffna en_US
dc.title Modified almost unbiased Liu estimator in logistic regression en_US
dc.type Article en_US


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