A model-based approach to estimation of finite population total using local linear polynomial regression estimator

dc.contributor.author	Kasungo, Kithikii
dc.date.accessioned	2012-02-01T08:22:39Z
dc.date.available	2012-02-01T08:22:39Z
dc.date.issued	2012-02-01
dc.description	A Dissertation Submitted in Partial Fulfilment of the Requirements for the Degree of Master of Science in Statistics ofKenyatta University: The QA 276.8.K3	en_US
dc.description.abstract	Estimation of finite population totals in the presence of auxiliary information is considered. A class of estimators based on local polynomial regression is proposed. Like generalized regression estimators, these estimators are weighted linear combination of study variables, in which the eights are calibrated to known control totals, but the assumptions on the super population model are considerably weaker. The estimators are shown to be asymptotically model-unbiased and consistent under mild assumptions. Simulation experiments indicate that the local polynomial regression estimator is more efficient than regression estimators when the model regression function is incorrectly specified, while being approximately as efficient when the parametric specification is correct.	en_US
dc.description.sponsorship	Kenyatta University	en_US
dc.identifier.uri	http://ir-library.ku.ac.ke/handle/123456789/2536
dc.language.iso	en	en_US
dc.subject	Estimation theory	en_US
dc.title	A model-based approach to estimation of finite population total using local linear polynomial regression estimator	en_US
dc.type	Thesis	en_US

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