Optimal generalized logistic estimator

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dc.contributor.authorVarathan, N.
dc.contributor.authorWijekoon, P.
dc.date.accessioned2021-11-29T04:30:33Z
dc.date.accessioned2022-06-28T06:46:05Z
dc.date.available2021-11-29T04:30:33Z
dc.date.available2022-06-28T06:46:05Z
dc.date.issued2018
dc.description.abstractIn this paper, we propose a new efficient estimator namely Optimal Generalized Logistic Estimator (OGLE) for estimating the parameter in a logistic regression model when there exists multicollinearity among explanatory variables. Asymptotic properties of the proposed estimator are also derived. The performance of the proposed estimator over the other existing estimators in respect of Scalar Mean Square Error crite rion is examined by conducting a Monte Carlo simulation.en_US
dc.identifier.urihttp://repo.lib.jfn.ac.lk/ujrr/handle/123456789/4271
dc.language.isoenen_US
dc.publisherUniversity of Jaffnaen_US
dc.subjectlogistic regression;en_US
dc.subjectbiaseden_US
dc.subjectmulticollinearityen_US
dc.subjectestimatoren_US
dc.subjectOptimal generalized logistic estimatoren_US
dc.subjectScalar mean square erroren_US
dc.titleOptimal generalized logistic estimatoren_US
dc.typeArticleen_US

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