Thresholding Projection Estimators in Functional Linear Models

Details Thresholding Projection Estimators in Functional Linear Models Thresholding Projection Estimators in Functional Linear Models

2008-06-03

arxiv.org/abs/0806.0533v2

Statistics

Methodology

Revised version for J. of Multivariate Analysis

Scientific paper

10.1016/j.jmva.2009.03.001

We consider the problem of estimating the regression function in functional linear regression models by proposing a new type of projection estimators which combine dimension reduction and thresholding. The introduction of a threshold rule allows to get consistency under broad assumptions as well as minimax rates of convergence under additional regularity hypotheses. We also consider the particular case of Sobolev spaces generated by the trigonometric basis which permits to get easily mean squared error of prediction as well as estimators of the derivatives of the regression function. We prove these estimators are minimax and rates of convergence are given for some particular cases.

Affiliated with

Also associated with

No associations

Rating

Thresholding Projection Estimators in Functional Linear Models 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 Thresholding Projection Estimators in Functional Linear Models, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Thresholding Projection Estimators in Functional Linear Models will most certainly appreciate the feedback.

Rate now

Comments { 0 }

Profile ID: LFWR-SCP-O-195473