## Modern Multivariate Statistical Analysis: A Graduate Course and Handbook |

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### Contents

MULTIVARIATE NORMAL AND SOME OTHER DISTRIBUTIONS | 1 |

WISHART DISTRIBUTION AND FUNCTIONS OF WISHART MATRICES | 59 |

5 | 69 |

Copyright | |

28 other sections not shown

### Common terms and phrases

according analysis approximation assume asymptotic expansion called central coefficient compute conditional consider constant CONTINUE Corollary correlation corresponding covariance matrix defined Definition derive determined discussed elements equal equation equivalent estimator Example expressed FORMAT formula function give given Hence hypothesis H independently distributed invariant joint known linear LR criterion mean vector method multiple multivariate noncentral nonsingular normal distribution Note null NUMBER observation obtain orthogonal matrix parameter population principal component probability problem procedure Proof Prove random rank region regression reject relation respectively result roots rule sample sample mean satisfying selection significance squares Statist subset Suppose symmetric symmetric matrix tables Theorem tion transformation unbiased values variables variance variates Wishart WRITE written x-distribution р р ი ი ი