A SIMPLE TEST OF NORMALITY FOR TIME SERIES

DOI10.1017/S0266466604204030zbMath1081.62066MaRDI QIDQ5719157

Carlos Velasco, Ignacio N. Lobato

Publication date: 17 January 2006

Published in: Econometric Theory (Search for Journal in Brave)

zbMATH Keywords

tables

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Time series, auto-correlation, regression, etc. in statistics (GARCH) (62M10)

Related Items

A random-projection based test of Gaussianity for stationary processes ⋮ White noise testing for functional time series ⋮ Distribution of test statistics under parameter uncertainty for time series data: an application to testing skewness, kurtosis and normality ⋮ On Sample Skewness and Kurtosis ⋮ Normality tests for dependent data: large-sample and bootstrap approaches ⋮ Principal Component Analysis of Spatially Indexed Functions ⋮ Tests of Normality of Functional Data ⋮ Normality test in random coefficient autoregressive models ⋮ Matrix-valued isotropic covariance functions with local extrema ⋮ A power study of goodness-of-fit tests for multivariate normality implemented in R ⋮ Behaviour of skewness, kurtosis and normality tests in long memory data

Cites Work

• Tests for departure from normality in the case of linear stochastic processes
• Testing that a stationary time series is Gaussian
• Limiting behavior of the ICF test for normality under Gram-Charlier alternatives
• A new approach to the BHEP tests for multivariate normality
• Goodness-of-fit tests for correlated data
• Inference-Without-Smoothing in the Presence of Nonparametric Autocorrelation
• An analysis of variance test for normality (complete samples)
• A test for normality based on the empirical characteristic function