A NOTE ON THE BEST INVARIANT ESTIMATOR
OF A DISTRIBUTION FUNCTION UNDER
THE KOLMOGOROV-SMIRNOV LOSS

ZHIQIANG CHEN AND ESWAR PHADIA

Department of Mathematics, William Paterson College of New Jersey,
Wayne, NJ 07470, U.S.A.

(Received February 23, 1996; revised May 13, 1996)

Abstract.    For the invariant decision problem of estimating a continuous distribution function with the Kolmogorov-Smirnov loss within the class of `proper' distribution functions, it is proved that the sample distribution function is the best invariant estimator only for the sample size n = 1 and 2. Further it is shown that the best invariant estimator is minimax. Exact jumps of the best invariant estimator are derived for n < 4.

Key words and phrases:    Best invariant estimator, Kolmogorov-Smirnov loss, minimaxity.

Source ( TeX , DVI , PS )