Estimating the mean and its effects on Neyman smooth tests of normality for ARMA models
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Publication:5507358
DOI10.1002/cjs.11292zbMath1352.62135OpenAlexW2466652631MaRDI QIDQ5507358
Pierre Lafaye de Micheaux, Pierre Duchesne, Joseph Tagne Tatsinkou
Publication date: 19 December 2016
Published in: Canadian Journal of Statistics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1002/cjs.11292
Asymptotic properties of parametric estimators (62F12) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Parametric hypothesis testing (62F03)
Related Items (4)
Goodness-of-fit tests for Laplace, Gaussian and exponential power distributions based on λ-th power skewness and kurtosis ⋮ Tests of Normality of Functional Data ⋮ Unnamed Item ⋮ On strong consistency and asymptotic normality of one-step Gauss-Newton estimators in ARMA time series models
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