28 October 1994 Class of time-domain procedures for testing that a stationary time series is Gaussian
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Abstract
In this contribution, a class of time-domain procedures for testing that a stationary time-series is Gaussian, is presented. These tests are based on minimum chi-square statistics in the deviations of certain sample statistics from their ensemble counterpart. Exact asymptotic distributions of these tests are derived under the null hypothesis of Gaussianity and under a class of local and fixed alternatives. Two specific tests are then developed, based respectively on the third-order and the fourth-order moments and on the characteristic functions. Extensive simulations are presented to illustrate the power of the test against various alternatives (including additive and non-additive contaminations and non-linear serial dependence.
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Eric Moulines, Eric Moulines, Karim Choukri, Karim Choukri, Jean-Francois Cardoso, Jean-Francois Cardoso, } "Class of time-domain procedures for testing that a stationary time series is Gaussian", Proc. SPIE 2296, Advanced Signal Processing: Algorithms, Architectures, and Implementations V, (28 October 1994); doi: 10.1117/12.190829; https://doi.org/10.1117/12.190829
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