Bandwidth choice and confidence intervals for derivatives of noisy data

1 December 1987

journal article
Published by Oxford University Press (OUP) in Biometrika

Vol. 74 (4) , 743-749
https://doi.org/10.1093/biomet/74.4.743

Abstract

We propose a method for automatic bandwidth selection for kernel estimators of derivatives of a regression function. The finite sample behaviour of this new method is compared with that of other methods in a Monte Carlo Study. The automatic estimation of derivatives can be employed for the construction of asymptotic local confidence intervals for the nonparametric estimate of the regression function and its first derivatives.

Keywords

BANDWIDTH SELECTION
CROSS-VALIDATION
DIFFERENCE QUOTIENT
ESTIMATION OF DERIVATIVES
FACTOR METHOD
KERNEL ESTIMATOR

This publication has 0 references indexed in Scilit: