Estimation of parameters of parallelism model with elliptically distributed errors

In this paper we consider some improved estimators of the intercept and slope parameters in a parallelism model with errors belonging to a sub-class of elliptically contoured distributions. We derive the exact bias, MSE matrices and quadratic risk expressions for these estimators. It is shown that the dominance properties of these estimators are the same as under normal theory. Further, it is shown that the shrinkage factor of the Stein estimators is robust with respect to the regression parameters and unknown mixing distributions.

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