Testing for a constant coefficient of variation in nonparametric regression

dc.creatorDette, H.
dc.creatorWieczorek, G.
dc.date2008-09-29
dc.date.accessioned2026-07-07T10:06:09Z
dc.date.available2026-07-07T10:06:09Z
dc.descriptionIn this paper we propose a new test for the hypothesis of a constant coefficient of variation in the common nonparametric regression model. The test is based on an estimate of the $L^2$-distance between the square of the regression function and variance function. We prove asymptotic normality of a standardized estimate of this distance under the null hypothesis and fixed alternatives and the finite sample properties of a corresponding bootstrap test are investigated by means of a simulation study. The results are applicable to stationary processes with the common mixing conditions and are used to construct tests for ARCH assumptions in financial time series.
dc.description29 pages
dc.identifierhttps://arxiv.org/abs/0809.4937
dc.identifierhttp://arxiv.org/abs/0809.4937
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/170226
dc.subjectStatistics Theory
dc.titleTesting for a constant coefficient of variation in nonparametric regression
dc.typetext

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