Authors: Dette, Holger
Hetzler, Benjamin
Title: A martingale-transform goodness-of-fit test for the form of the conditional variance
Language (ISO): en
Abstract: In the common nonparametric regression model the problem of testing for a specific para- metric form of the variance function is considered. Recently Dette and Hetzler (2008) proposed a test statistic, which is based on an empirical process of pseudo residuals. The process converges weakly to a Gaussian process with a complicated covariance kernel depending on the data generating process. In the present paper we consider a standardized version of this process and propose a martingale transform to obtain asymptotically distribution free tests for the corresponding Kolmogorov-Smirnov and Cramer-von-Mises functionals. The finite sample properties of the proposed tests are investigated by means of a simulation study.
Subject Headings: Conditional variance
Goodness-of-fit test
Martingale transform
Nonparametric regression
Issue Date: 2008-11-26T14:35:29Z
Appears in Collections:Sonderforschungsbereich (SFB) 475

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