Resource title

new test for the parametric form of the variance function in nonparametric regression

Resource image

image for OpenScout resource :: new test for the parametric form of the variance function in nonparametric regression

Resource description

In the common nonparametric regression model the problem of testing for the parametric form of the conditional variance is considered. A stochastic process based on the difference between the empirical processes obtained from the standardized nonparametric residuals under the null hypothesis (of a specific parametric form of the variance function) and the alternative is introduced and its weak convergence established. This result is used for the construction of a Cramer von Mises type statistic for testing the parametric form of the conditional variance. The finite sample properties of a bootstrap version of this test are investigated by means of a simulation study. In particular the new procedure is compared with some of the currently available methods for this problem and its performance is illustrated by means of a data example.

Resource author

Holger Dette, Ingrid van Keilegom

Resource publisher

Resource publish date

Resource language

eng

Resource content type

text/html

Resource resource URL

http://hdl.handle.net/10419/22622

Resource license

Adapt according to the presented license agreement and reference the original author.