Asymptotic normality of the Parzen-Rosenblatt density estimator for strongly mixing random fields

Details Asymptotic normality of the Parzen-Rosenblatt density estimator for strongly mixing random fields Asymptotic normality of the Parzen-Rosenblatt density estimator for strongly mixing random fields

2010-08-07

arxiv.org/abs/1008.1342v1

Mathematics

Statistics Theory

16 pages

Scientific paper

We prove the asymptotic normality of the kernel density estimator (introduced by Rosenblatt (1956) and Parzen (1962)) in the context of stationary strongly mixing random fields. Our approach is based on the Lindeberg's method rather than on Bernstein's small-block-large-block technique and coupling arguments widely used in previous works on nonparametric estimation for spatial processes. Our method allows us to consider only minimal conditions on the bandwidth parameter and provides a simple criterion on the (non-uniform) strong mixing coefficients which do not depend on the bandwith.

Affiliated with

Also associated with

No associations

Rating

Asymptotic normality of the Parzen-Rosenblatt density estimator for strongly mixing random fields 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 Asymptotic normality of the Parzen-Rosenblatt density estimator for strongly mixing random fields, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Asymptotic normality of the Parzen-Rosenblatt density estimator for strongly mixing random fields will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-593828