Testing for Hermite rank in Gaussian subordination processes

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BERAN, Jan, Sven MÖHRLE, Sucharita GHOSH, 2016. Testing for Hermite rank in Gaussian subordination processes. In: Journal of Computational and Graphical Statistics. 25(3), pp. 917-934. ISSN 1061-8600. eISSN 1537-2715. Available under: doi: 10.1080/10618600.2015.1056345

@article{Beran2016-08-05Testi-33448, title={Testing for Hermite rank in Gaussian subordination processes}, year={2016}, doi={10.1080/10618600.2015.1056345}, number={3}, volume={25}, issn={1061-8600}, journal={Journal of Computational and Graphical Statistics}, pages={917--934}, author={Beran, Jan and Möhrle, Sven and Ghosh, Sucharita} }

eng 2016-03-24T08:53:26Z 2016-03-24T08:53:26Z Ghosh, Sucharita 2016-08-05 Ghosh, Sucharita Testing for Hermite rank in Gaussian subordination processes Statistical inference for time series with long-range dependence is often based on the assumption of Gaussian subordination X<sub>t</sub> = G(Z<sub>t</sub>). Although the Hermite rank m of G plays an essential role for statistical inference in these situations, the question of estimating m or of testing hypotheses about the Hermite rank has not been addressed in the literature. In this paper, a method is introduced for testing H<sub>0</sub>: m = 1 against H<sub>1</sub>: m > 1. This allows for deciding whether inference based on the usual assumption of m = 1 is appropriate. Simulations and data examples illustrate the method. Möhrle, Sven Beran, Jan Möhrle, Sven Beran, Jan

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