Accession Number : AD0785448

Title :   Best Linear Unbiased and Invariant Estimators for Regression Parameters Based on Ordered Observations.

Descriptive Note : Technical rept.,

Corporate Author : KENTUCKY UNIV LEXINGTON DEPT OF STATISTICS

Personal Author(s) : Govindarajulu,Z.

Report Date : JUN 1974

Pagination or Media Count : 20

Abstract : The best linear unbiased estimators of the parameters in the multiple regression model are obtained when the samples are arbitrarily censored. The homogeneity of variance, polynomial regression and simple linear regression become special cases of the above model. The formulas take simpler forms when the underlying distribution is symmetric and the subsamples are of equal size and are symmetrically censored. Best constant-risk estimators of the parameters alpha, beta, and sigma in the simple linear regression model are obtained. These results are applied to symmetric uniform and negative exponential cases. (Author)

Descriptors :   *Regression analysis, *Sampling, Distribution functions, Estimates, Theorems

Subject Categories : Statistics and Probability

Distribution Statement : APPROVED FOR PUBLIC RELEASE