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 |
URI: | http://hdl.handle.net/2003/25870 http://dx.doi.org/10.17877/DE290R-14287 |
Issue Date: | 2008-11-26T14:35:29Z |
Appears in Collections: | Sonderforschungsbereich (SFB) 475 |
Files in This Item:
File | Description | Size | Format | |
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tr07-08-Dette.pdf | DNB | 204.85 kB | Adobe PDF | View/Open |
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