ESTIMATION IN MULTIFACTOR POLYNOMIAL REGRESSION UNDER NON-NORMALITY

Date

2010-01-10

Author

Tiku, Moti L.
Akkaya, Ayşen

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Modified maximum likelihood estimators of the parameters in a second order polynomial regression model are derived. They are shown to be considerably more efficient and robust than the commonly used least squares estimators. Real life examples are given.

Subject Keywords

Non-normality, Maximum likelihood, Modified maximum likelihood, Robustness, Polynomial regression, Outliers, Inliers

URI

https://hdl.handle.net/11511/55733

Journal

PAKISTAN JOURNAL OF STATISTICS

Collections

Department of Statistics, Article

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Citation Formats

M. L. Tiku and A. Akkaya, “ESTIMATION IN MULTIFACTOR POLYNOMIAL REGRESSION UNDER NON-NORMALITY,” PAKISTAN JOURNAL OF STATISTICS, pp. 49–68, 2010, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/55733.