THE OPTIMAL STEIN ESTIMATION RELATIVE TO CONCENTRATION PROBABILITY – A LARGE SAMPLE APPROXIMATION

Raman Pant

Resumen


General family of Stein rule estimators is considered in linear regression model. The large sample approximation of its sampling
distribution is derived. Approximations of concentration probability of the estimators around the true value are evaluated.
Optimal selection of the biasing scalar is discussed.

KEYWORDS : Linear regression model, Stein rule estimator, large sample approximation, Sampling distribution, concentration
probability

MSC: 62F10


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