"David Jones" <[EMAIL PROTECTED]> wrote in message news:<[EMAIL PROTECTED]>... > The above has overlooked a number of possibilities: > > (i) use of a Kernel estimate for the distribution function (as a > non-parametric estimate alternative to just using the sample > quantile).
I once asked Matt Wand (of Wand, MP & MC Jones, Kernel Smoothing, Chapman & Hall, London, 1995) about this and he suggested that generally you don't want to do this and would usually be better just to use the sample quantile (if you can specify enough about your distribution that you can be confident your kernel estimate of the quantile is better, you can often use that information more directly to get a better directly-based-on-sample estimate). (That's not to say you'd never use a kernel based estimate.) Glen . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
