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PRETEST ESTIMATION OF LINEAR REGRSSION MODEL FOR INCOMPLETE DATA | ||
| AL-TAQANI | ||
| Article 1, Volume 18, Issue 4, 2005, Pages 0-0 | ||
| Abstract | ||
| In statistical analysis, the problem of estimating the parameters of simple linear model is when we have incomplete data and the resulting estimators are inefficient. Many methods are found by researchers to treat such problem. In this work, we study two of these methods when using incomplete data namely, complete case analysis and available case analysis. A new procedure is suggested called shrinkage estimator which connects between estimate parameters of linear model and those two methods by using constant function. The bias, MSE and RE for the estimators of the parameters of simple linear model are found also, the values of these estimators are calculated | ||
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