Testing Normality for Linear AR(p) Models

DOI10.1081/STA-120028732zbMath1066.62048MaRDI QIDQ3155301

Hueng Wong, Min Chen, Wai-Cheung Ip

Publication date: 14 January 2005

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

zbMATH Keywords

power study

Mathematics Subject Classification ID

Nonparametric hypothesis testing (62G10) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10) Asymptotic properties of nonparametric inference (62G20)

Related Items (1)

Characteristic function-based hypothesis tests under weak dependence

Cites Work

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• Tests for departure from normality in the case of linear stochastic processes
• Autocorrelation, autoregression and autoregressive approximation
• Tests for Gaussianity and linearity of multivariate stationary time series
• A mixed-type test for linearity in time series
• Forward and reversed time prediction of autoregressive sequences
• Testing normality in autoregressive models
• A Test of Goodness of Fit
• A test for normality based on the empirical characteristic function

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