Applied Multivariate Analysis

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Includes practical elements of matrix theory, continuous multivariate distributions and basic multivariate statistics in the normal distribution, regression and the analysis of variance, factor analysis and latent structure analysis, canonical correlations, stable portfolio analysis, classifications and discrimination models, control in the multivariate linear model, and structuring multivariate populations. 1982 edition.