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

DOI10.1007/s11203-013-9087-9zbMath1292.62130OpenAlexW2113673756MaRDI QIDQ376708

Joseph Ngatchou-Wandji, Michel Harel

Publication date: 19 November 2013

Published in: Statistical Inference for Stochastic Processes (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11203-013-9087-9

zbMATH Keywords

symmetrytestingfunctional limit theoremnonstationarityabsolute regularityheteroscedastic models

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Functional limit theorems; invariance principles (60F17)

Related Items (8)

Testing symmetry based on empirical likelihood ⋮ A nonparametric model check for time series when the random vectors are nonstationary and absolutely regular ⋮ On a new goodness-of-fit test for the Rayleigh distribution based on a conditional expectation characterization ⋮ A Monte Carlo evaluation of the performance of two new tests for symmetry ⋮ Testing for serial independence in vector autoregressive models ⋮ Fourier inference for stochastic volatility models with heavy-tailed innovations ⋮ Asymptotic behavior of nonparametric estimators of the two-dimensional and bivariate renewal functions ⋮ Testing nonstationary and absolutely regular nonlinear time series models

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