Abstract

Preface to the Third Edition.Preface to the Second Edition.Preface to the First Edition.1. Introduction.2. The Multivariate Normal Distribution.3. Estimation of the Mean Vector and the Covariance Matrix.4. The Distributions and Uses of Sample Correlation Coefficients.5. The Generalized T2-Statistic.6. Classification of Observations.7. The Distribution of the Sample Covariance Matrix and the Sample Generalized Variance.8. Testing the General Linear Hypothesis: Multivariate Analysis of Variance9. Testing Independence of Sets of Variates.10. Testing Hypotheses of Equality of Covariance Matrices and Equality of Mean Vectors and Covariance Matrices.11. Principal Components.12. Cononical Correlations and Cononical Variables.13. The Distributions of Characteristic Roots and Vectors.14. Factor Analysis.15. Pattern of Dependence Graphical Models.Appendix A: Matrix Theory.Appendix B: Tables.References.Index.

Keywords

MathematicsCovariance matrixEstimation of covariance matricesStatisticsMultivariate normal distributionScatter matrixCovarianceStatisticMultivariate statisticsLaw of total covarianceTest statisticPrincipal component analysisApplied mathematicsStatistical hypothesis testingCovariance intersection

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Publication Info

Year
1986
Type
article
Volume
4
Issue
1
Pages
135-135
Citations
9231
Access
Closed

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Robb J. Muirhead, T. W. Anderson (1986). An Introduction to Multivariate Statistical Analysis. Journal of Business and Economic Statistics , 4 (1) , 135-135. https://doi.org/10.2307/1391399

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DOI
10.2307/1391399