A Cramér-von Mises test for symmetry of the error distribution in asymptotically stationary stochastic models

This paper has to do with a Cramér-von Mises test for symmetry of the error distribution in a class of absolutely regular and non-necessarily stationary heteroscedastic models. The test statistic is based on the empirical characteristic function. Its convergence, as well as that of the residual-base...

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Bibliographic Details
Published in:Statistical inference for stochastic processes : an international journal devoted to time series analysis and the statistics of continuous time processes and dynamic systems 2013-10, Vol.16 (3), p.207-236
Main Authors: Ngatchou-Wandji, Joseph, Harel, Michel
Format: Article
Language:English
Subjects:
Mathematics
Mathematics and Statistics
Probability Theory and Stochastic Processes
Statistical Theory and Methods
Statistics
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Summary:This paper has to do with a Cramér-von Mises test for symmetry of the error distribution in a class of absolutely regular and non-necessarily stationary heteroscedastic models. The test statistic is based on the empirical characteristic function. Its convergence, as well as that of the residual-based empirical distribution function are established. From these results, the null cumulative distribution function of the test statistic is approximated. A simulation experiment shows that the test performs well on the examples tested.
ISSN:1387-0874
1572-9311
DOI:10.1007/s11203-013-9087-9