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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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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 |
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container_title | Statistical inference for stochastic processes : an international journal devoted to time series analysis and the statistics of continuous time processes and dynamic systems |
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creator | Ngatchou-Wandji, Joseph Harel, Michel |
description | 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. |
doi_str_mv | 10.1007/s11203-013-9087-9 |
format | article |
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language | eng |
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source | Springer Nature |
subjects | Mathematics Mathematics and Statistics Probability Theory and Stochastic Processes Statistical Theory and Methods Statistics |
title | A Cramér-von Mises test for symmetry of the error distribution in asymptotically stationary stochastic models |
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