On Derivation of The Semi-Parametric Weighted Likelihood Estimator, SPW, and the Weighted Conditional Pseudo Likelihood Estimator, WCPE

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dc.contributor.authorKamun, Samuel Joel
dc.contributor.authorSimwa, Richard Onyino
dc.contributor.authorSewe, Stanley
dc.date.accessioned2024-09-18T09:23:36Z
dc.date.available2024-09-18T09:23:36Z
dc.date.issued2021
dc.descriptionJournal Article
dc.description.abstractThe aim of our study is to devise systems of weighted regression estimating equations for estimating the coefficients of weighted likelihood regression estimators. We constructed the system of weighted regression estimating equations, using different modified and unmodified weights. The study has come up with two new estimators, the semi-parametric weighted likelihood estimator, SPW and the weighted conditional pseudo-likelihood estimator, WCPE.
dc.identifier.citationKamun, S. J., Simwa, R. O., & Sewe, S. ( 2021). On Derivation of The Semi-Parametric Weighted Likelihood Estimator, SPW, and the Weighted Conditional Pseudo Likelihood Estimator, WCPE. Far East Journal of Theoretical Statistics
dc.identifier.issn0972-0863
dc.identifier.urihttps://repository.daystar.ac.ke/handle/123456789/5161
dc.language.isoen
dc.publisherFar East Journal of Theoretical Statistics
dc.relation.ispartofseries62(2)
dc.subjectweighted regression estimating equations
dc.subjectweighted likelihood estimators.
dc.titleOn Derivation of The Semi-Parametric Weighted Likelihood Estimator, SPW, and the Weighted Conditional Pseudo Likelihood Estimator, WCPE
dc.typeArticle

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