
Abstract
The present article deals with the problem of estimation of parameters in a linear regression model when some data on response variable is missing and the responses are equicorrelated. The ordinary least squares and optimal homogeneous predictors are employed to find the imputed values of missing observations. Their efficiency properties are analyzed using the small disturbances asymptotic theory. The estimation of regression coefficients using these imputed values is also considered and a comparison of estimators is presented.
Item Type: | Paper |
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Faculties: | Mathematics, Computer Science and Statistics > Statistics > Collaborative Research Center 386 Special Research Fields > Special Research Field 386 |
Subjects: | 500 Science > 510 Mathematics |
URN: | urn:nbn:de:bvb:19-epub-1562-6 |
Language: | English |
Item ID: | 1562 |
Date Deposited: | 04. Apr 2007 |
Last Modified: | 04. Nov 2020, 12:45 |