Score tests for heteroscedasticity in wavelet regression

Abstract

We consider two score tests for heteroscedasticity in the errors of a signal-plus-noise model, where the signal is estimated by wavelet thresholding methods. The error variances are assumed to depend on observed covariates, through a parametric relationship of known form. The tests are based on the approaches of Breusch & Pagan (1979) and Koenker (1981). We establish the asymptotic validity of the tests and examine their performance in a simulation study. The Koenker test is found to perform well, in terms of both size and power.

Department(s)

Mathematics

Document Type

Article

DOI

https://doi.org/10.1093/biomet/85.1.229

Keywords

De-noising, Signal extraction, Thresholding

Publication Date

1-1-1998

Journal Title

Biometrika

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