Distribution Free Goodness-of-Fit Tests for Linear Processes

This article proposes a class of goodness-of-fit tests for the autocorrelation function of a time series process, including those exhibiting long-range dependence. Test statistics for composite hypotheses are functionals of a (approximated) martingale transformation of the Bartlett's Tp-process with estimated parameters, which converges in distribution to the standard Brownian Motion under the null hypothesis. We discuss tests of different nature such as omnibus, directional and Portmanteau-type tests. A Monte Carlo study illustrates the performance of the different tests in practice

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Year of publication:	[2008]
Authors:	Delgado, Miguel A.
Other Persons:	Hidalgo, Javier S. (contributor) ; Velasco, Carlos (contributor)
Publisher:	[2008]: [S.l.] : SSRN
Subject:	Statistischer Test \| Statistical test \| Theorie \| Theory \| Regressionsanalyse \| Regression analysis \| Statistische Verteilung \| Statistical distribution