Analytic Bias Reduction for $k$-Sample Functionals

Details Analytic Bias Reduction for $k$-Sample Functionals Analytic Bias Reduction for $k$-Sample Functionals

2009-03-17

arxiv.org/abs/0903.2889v1

Statistics

Methodology

Scientific paper

We give analytic methods for nonparametric bias reduction that remove the need for computationally intensive methods like the bootstrap and the jackknife. We call an estimate {\it $p$th order} if its bias has magnitude $n_0^{-p}$ as $n_0 \to \infty$, where $n_0$ is the sample size (or the minimum sample size if the estimate is a function of more than one sample). Most estimates are only first order and require O(N) calculations, where $N$ is the total sample size. The usual bootstrap and jackknife estimates are second order but they are computationally intensive, requiring $O(N^2)$ calculations for one sample. By contrast Jaeckel's infinitesimal jackknife is an analytic second order one sample estimate requiring only O(N) calculations. When $p$th order bootstrap and jackknife estimates are available, they require $O(N^p)$ calculations, and so become even more computationally intensive if one chooses $p>2$. For general $p$ we provide analytic $p$th order nonparametric estimates that require only O(N) calculations. Our estimates are given in terms of the von Mises derivatives of the functional being estimated, evaluated at the empirical distribution. For products of moments an unbiased estimate exists: our form for this "polykay" is much simpler than the usual form in terms of power sums.

Affiliated with

Also associated with

No associations

Rating

Analytic Bias Reduction for $k$-Sample Functionals does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Analytic Bias Reduction for $k$-Sample Functionals, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Analytic Bias Reduction for $k$-Sample Functionals will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-490968