Compact Matrix Expressions for Generalized Wald Tests of Equality of Moment Vectors,
AbstractAsymptotic chi-squared test statistics for testing the equality of moment vectors are developed. The test statistics proposed are generalized Wald test statistics that specialize for different settings by inserting an appropriate asymptotic variance matrix of sample moments. Scaled test statistics are also considered for dealing with nonstandard conditions. The specialization will be carried out for testing the equality of multinomial populations, and the equality of variance and correlation matrices for both normal and nonnormal data. When testing the equality of correlation matrices, a scaled version of the normal theory chi-squared statistic is proven to be an asymptotically exact chi-squared statistic in the case of elliptical data.
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Bibliographic InfoArticle provided by Elsevier in its journal Journal of Multivariate Analysis.
Volume (Year): 63 (1997)
Issue (Month): 2 (November)
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Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description
Other versions of this item:
- Albert Satorra & Heinz Neudecker, 1995. "Compact matrix expressions for generalized Wald tests of equality of moment vectors," Economics Working Papers 127, Department of Economics and Business, Universitat Pompeu Fabra.
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Andrews, Donald W. K., 1987.
"Asymptotic Results for Generalized Wald Tests,"
Cambridge University Press, vol. 3(03), pages 348-358, June.
- Heinz Neudecker & Albert Satorra, 1995.
"The algebraic equality of two asymptotic tests for the hypothesis that a normal distribution has a specified correlation matrix,"
Economics Working Papers
131, Department of Economics and Business, Universitat Pompeu Fabra.
- Neudecker, Heinz & Satorra, Albert, 1996. "The algebraic equality of two asymptotic tests for the hypothesis that a normal distribution has a specified correlation matrix," Statistics & Probability Letters, Elsevier, vol. 30(2), pages 99-103, October.
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