A Cramér-von Mises test for symmetry of the error distribution in asymptotically stationary stochastic models
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DOI: 10.1007/s11203-013-9087-9
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"A bootstrap approach to test the conditional symmetry in time series models,"
Computational Statistics & Data Analysis, Elsevier, vol. 51(7), pages 3484-3504, April.
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Cited by:
- Michel Harel & Livasoa Andriamampionona & Victor Harison, 2019. "Asymptotic behavior of nonparametric estimators of the two-dimensional and bivariate renewal functions," Statistical Inference for Stochastic Processes, Springer, vol. 22(3), pages 499-523, October.
- James S. Allison & Charl Pretorius, 2017. "A Monte Carlo evaluation of the performance of two new tests for symmetry," Computational Statistics, Springer, vol. 32(4), pages 1323-1338, December.
- Joseph Ngatchou-Wandji & Madan L. Puri & Michel Harel & Echarif Elharfaoui, 2019. "Testing nonstationary and absolutely regular nonlinear time series models," Statistical Inference for Stochastic Processes, Springer, vol. 22(3), pages 557-593, October.
- Bruno Ebner & Bernhard Klar & Simos G. Meintanis, 2018. "Fourier inference for stochastic volatility models with heavy-tailed innovations," Statistical Papers, Springer, vol. 59(3), pages 1043-1060, September.
- Simos G. Meintanis & Joseph Ngatchou-Wandji & James Allison, 2018. "Testing for serial independence in vector autoregressive models," Statistical Papers, Springer, vol. 59(4), pages 1379-1410, December.
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More about this item
Keywords
Nonstationarity; Absolute regularity; Functional limit theorem; Heteroscedastic models; Symmetry; Testing; 62M10; 60F17; 62G10;All these keywords.
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Statistics
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