A Generalized Portmanteau Goodness-of-Fit Test for Time Series Models

30 Pages Posted: 31 Oct 2008

See all articles by Willa W. Chen

Willa W. Chen

Texas A&M University - Department of Statistics

Date Written: 2000

Abstract

We present a goodness of fit test for time series models based on the discrete spectral averageestimator. Unlike current tests of goodness of fit, the asymptotic distribution of our test statisticallows the null hypothesis to be either a short or long range dependence model. Our test isin the frequency domain, is easy to compute and does not require the calculation of residualsfrom the fitted model. This is especially advantageous when the fitted model is not a finiteorder autoregressive model. The test statistic is a frequency domain analogue of the test byHong (1996) which is a generalization of the Box-Pierce (1970) test statistic. A simulation studyshows that our test has power comparable to that of Hong's test and superior to that of anotherfrequency domain test by Milhoj (1981).

Keywords: Portmanteau test, long memory, goodness-of-fit

Suggested Citation

Chen, Willa W., A Generalized Portmanteau Goodness-of-Fit Test for Time Series Models (2000). Statistics Working Papers Series, Vol. , pp. -, 2000. Available at SSRN: https://ssrn.com/abstract=1290970

Willa W. Chen (Contact Author)

Texas A&M University - Department of Statistics ( email )

155 Ireland Street
447 Blocker
College Station, TX 77843
United States

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