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Characterizations of multivariate normality. I. Through independence of some statistics

Author

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  • Khatri, C. G.
  • Rao, C. Radhakrishna

Abstract

It is established that a vector variable (X1, ..., Xk) has a multivariate normal distribution if for each Xi the regression on the rest is linear and the conditional distribution about the regression does not depend on the rest of the variables, provided the regression coefficients satisfy some mild conditions. The result is extended to the case where Xi themselves are vector variables.

Suggested Citation

  • Khatri, C. G. & Rao, C. Radhakrishna, 1976. "Characterizations of multivariate normality. I. Through independence of some statistics," Journal of Multivariate Analysis, Elsevier, vol. 6(1), pages 81-94, March.
    • Handle: RePEc:eee:jmvana:v:6:y:1976:i:1:p:81-94
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    Cited by:

    1. Anindya Bhadra & Arvind Rao & Veerabhadran Baladandayuthapani, 2018. "Inferring network structure in non†normal and mixed discrete†continuous genomic data," Biometrics, The International Biometric Society, vol. 74(1), pages 185-195, March.

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