On rate optimal local estimation in functional linear model

Mathematics – Statistics Theory

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

Major revision

Scientific paper

We consider the estimation of the value of a linear functional of the slope parameter in functional linear regression, where scalar responses are modeled in dependence of random functions. The theory in this paper covers in particular point-wise estimation as well as the estimation of weighted averages of the slope parameter. We propose a plug-in estimator which is based on a dimension reduction technique and additional thresholding. It is shown that this estimator is consistent under mild assumptions. We derive a lower bound for the maximal mean squared error of any estimator over a certain ellipsoid of slope parameters and a certain class of covariance operators associated with the regressor. It is shown that the proposed estimator attains this lower bound up to a constant and hence it is minimax optimal. Our results are appropriate to discuss a wide range of possible regressors, slope parameters and functionals. They are illustrated by considering the point-wise estimation of the slope parameter or its derivatives and its average value over a given interval.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

On rate optimal local estimation in functional linear model 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 On rate optimal local estimation in functional linear model, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and On rate optimal local estimation in functional linear model will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-553067

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.