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Technometrics, 2003
(2003). Testing for Normality. Journal of the American Statistical Association: Vol. 98, No. 463, pp. 765-765.
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(2003). Testing for Normality. Journal of the American Statistical Association: Vol. 98, No. 463, pp. 765-765.
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IEEE Transactions on Information Theory, 1992
Summary: The problem of deciding whether a sample of a random field was generated by a Gaussian distribution is considered. Based on extensions of large deviations estimates due to \textit{M. D. Donsker} and \textit{S. R. S. Varadhan} [Commun. Math. Phys.
Yossef Steinberg, Ofer Zeitouni
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Summary: The problem of deciding whether a sample of a random field was generated by a Gaussian distribution is considered. Based on extensions of large deviations estimates due to \textit{M. D. Donsker} and \textit{S. R. S. Varadhan} [Commun. Math. Phys.
Yossef Steinberg, Ofer Zeitouni
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Testing multivariate normality
Biometrika, 1978SUMMARY Previous work on testing multivariate normality is reviewed. Coordinate-dependent and invariant procedures are distinguished. The arguments for concentrating on tests of linearity of regression are indicated and such tests, both coordinate-dependent and invariant, are developed.
Cox, D. R., Small, N. J. H.
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