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Estimation In The Simple Linear Regression Model With One-fold Nested Error

In this thesis, estimation in simple linear regression model with one-fold nested error is studied.
To estimate the fixed effect parameters, generalized least squares and maximum likelihood estimation procedures are reviewed. Moreover, Minimum Norm Quadratic Estimator (MINQE), Almost Unbiased Estimator (AUE) and Restricted Maximum Likelihood Estimator (REML) of variance of primary units are derived.
Also, confidence intervals for the fixed effect parameters and the variance components are studied. Finally, the aforesaid estimation techniques and confidence intervals are applied to a real-life data and the results are presented

Identiferoai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/3/12606171/index.pdf
Date01 June 2005
CreatorsUlgen, Burcin Emre
ContributorsGuven, Bilgehan
PublisherMETU
Source SetsMiddle East Technical Univ.
LanguageEnglish
Detected LanguageEnglish
TypeM.S. Thesis
Formattext/pdf
RightsTo liberate the content for public access

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