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

Joseph Ngatchou-Wandji () and Michel Harel

Statistical Inference for Stochastic Processes, 2013, vol. 16, issue 3, 207-236

Abstract: 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. Copyright Springer Science+Business Media Dordrecht 2013

Keywords: Nonstationarity; Absolute regularity; Functional limit theorem; Heteroscedastic models; Symmetry; Testing; 62M10; 60F17; 62G10 (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (5)

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DOI: 10.1007/s11203-013-9087-9

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