Asymptotically invariant Gaussianity test for causal invertible time series
نویسندگان
چکیده
This paper introduces a Gaussianity test for causal invertible time series. It is based on a quadratic form in di erences between sample means and expected values of certain nite memory nonlinear functions of the estimated innovation sequence. The test has, by construction, an interesting property: under reasonable assumptions on the regularity of the stationary process, it is asymptotically invariant with respect to the spectral density of the process. Monte-Carlo experiments are included to illustrate the proposed approach.
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