Estimation in the simple linear regression model with one-fold nested error

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2005

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Ülgen, Burçin Emre

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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

Subject Keywords

Theory and method of social science statistics.

URI

http://etd.lib.metu.edu.tr/upload/3/12606171/index.pdf
https://hdl.handle.net/11511/15162

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Graduate School of Natural and Applied Sciences, Thesis

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Citation Formats

B. E. Ülgen, “Estimation in the simple linear regression model with one-fold nested error,” M.S. - Master of Science, Middle East Technical University, 2005.