Testing that a stationary time-series is Gaussian: time-domain vs. frequency-domain approaches
- 31 December 2002
- conference paper
- Published by Institute of Electrical and Electronics Engineers (IEEE)
- p. 336-340
- https://doi.org/10.1109/host.1993.264540
Abstract
Several frequency-domain and time-domain procedures for testing that a stationary time-series are Gaussian are presented. Closed-form expressions of the asymptotic distribution of the test statistics under the null hypothesis of Gaussianity are derived. These procedures are then compared and assessed in two typical examples of applications (i) the detection of additive non-Gaussian outliers in stationary Gaussian noise with unknown covariance and (ii) the detection of the presence of contaminating values from non-symmetric distributions.Keywords
This publication has 8 references indexed in Scilit:
- Testing that a multivariate stationary time-series is GaussianPublished by Institute of Electrical and Electronics Engineers (IEEE) ,2003
- Testing That a Stationary Time Series is GaussianThe Annals of Statistics, 1987
- The Effect of Dependence on Chi-Squared and Empiric Distribution Tests of FitThe Annals of Statistics, 1983
- TESTING FOR GAUSSIANITY AND LINEARITY OF A STATIONARY TIME SERIESJournal of Time Series Analysis, 1982
- A spectral method for confidence interval generation and run length control in simulationsCommunications of the ACM, 1981
- A TEST FOR LINEARITY OF STATIONARY TIME SERIESJournal of Time Series Analysis, 1980
- Goodness-of-fit tests for correlated dataBiometrika, 1975
- Tests for departure from normality in the case of linear stochastic processesMetrika, 1961