Applied multivariate statistical analysis, Volume 1
This market-leading book offers a readable introduction to the statistical analysis of multivariate observations. Its overarching goal is to provide readers with the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Chapter topics include aspects of multivariate analysis, matrix algebra and random vectors, sample geometry and random sampling, the multivariate normal distribution, inferences about a mean vector, comparisons of several multivariate means, multivariate linear regression models, principal components, factor analysis and inference for structured covariance matrices, canonical correlation analysis, and discrimination and classification. For experimental scientists in a variety of disciplines.
29 pages matching likelihood ratio in this book
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a very comphrehensive and in-dept monograph, good multivariate statistical handbook for research or grad studies.
Review: Applied Multivariate Statistical AnalysisUser Review - Joecolelife - Goodreads
There have been many good theoretical texts on multivariate analysis including Anderson, Eaton and Gnandesikan. Tabachnick has written a popular applied text for the social sciences. Yet for many ... Read full review
ASPECTS OF MULTIVARIATE ANALYSIS
MATRIX ALGEBRA AND RANDOM VECTORS
SAMPLE GEOMETRY AND RANDOM SAMPLING
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