Bandwidth selection in kernel density estimation: oracle inequalities and adaptive minimax optimality

Details Bandwidth selection in kernel density estimation: oracle inequalities and adaptive minimax optimality Bandwidth selection in kernel density estimation: oracle inequalities and adaptive minimax optimality

2010-09-06

arxiv.org/abs/1009.1016v1

Mathematics

Statistics Theory

Scientific paper

We address the problem of density estimation with $\bL_p$--loss by selection of kernel estimators. We develop a selection procedure and derive corresponiding $\bL_p$--risk oracle inequalities. It is shown that the proposed selection rule leads to the minimax estimator that is adaptive over a scale of the anisotropic Nikol'ski classes. The main technical tools used in our derivations are uniform bounds on the $\bL_p$--norms of empirical processes developed recently in Goldenshluger and Lepski~(2010).

Affiliated with

Also associated with

No associations

Rating

Bandwidth selection in kernel density estimation: oracle inequalities and adaptive minimax optimality 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 Bandwidth selection in kernel density estimation: oracle inequalities and adaptive minimax optimality, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Bandwidth selection in kernel density estimation: oracle inequalities and adaptive minimax optimality will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-297905