The Annals of Statistics

Estimating a Regression Function

Sara van de Geer

Abstract

In this paper, an entropy approach is proposed to establish rates of convergence for estimators of a regression function. General regression problems are considered, with linear regression, splines and isotonic regression as special cases. The estimation methods studied are least squares, least absolute deviations and penalized least squares. Common features of these methods and various regression problems are highlighted.

Article information

Source
Ann. Statist., Volume 18, Number 2 (1990), 907-924.

Dates
First available in Project Euclid: 12 April 2007

https://projecteuclid.org/euclid.aos/1176347632

Digital Object Identifier
doi:10.1214/aos/1176347632

Mathematical Reviews number (MathSciNet)
MR1056343

Zentralblatt MATH identifier
0709.62040

JSTOR
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