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Multivariate statistical methods provide a powerful tool for analyzing data when observations are taken over a period of time on the same subject. With the advent of fast and efficient computers and the availability of computer packages such as S-plus and SAS, multivariate methods once too complex to tackle are now within reach of most researchers and data analysts. With an emphasis on computing techniques in combination with a full understanding of the mathematics behind the methods, Methods of Multivariate Statistics offers an up-to-date account of multivariate methods. Focusing on the maximum likelihood method for estimation, testing of hypotheses, and " profile analysis, " this book offers comprehensive discussions of commonly encountered multivariate data and also covers some practical and important problems lacking in other texts. These include:
With clear chapter introductions and numerous problem sets, Methods of Multivariate Statistics meets every statistician’ s need for a comprehensive investigation of the latest methods in multivariate statistics.
Abbreviations and Notations. Preface. Multivariate Methods: An Overview. Multivariate Normal Distributions. Outliers Detection and Normality Check. Inference on Location--Hotelling's T2. Repeated Measures. Multivariate Analysis of Variance. Profile Analysis. Classification and Discrimination. Multivariate Regression. Growth Curve Models. Principal Component Analysis. Factor Analysis. Inference on Covariance Matrices. Correlations. Missing Observations: General Case. Missing Observations: Monotone Sample. Bootstrapping. Imputting Missing Data. Some Results on Matrices. Tables. Bibliography.
MUNI SHANKER SRIVASTAVA, PhD, is a Professor in the Department of Statistics at the University of Toronto. He is an Elected Member of the International Statistics Institute, a Fellow of the Institute of Mathematical Statistics, a Fellow of the Royal Statistical Society, and a Fellow of the American Statistical Association.
"...an excellent book...one of the best references for its level." (Technometrics, Vol. 45, No. 1, February 2003) "...a very useful, well-written, and interesting book...an excellent book; highly recommended." (Choice, Vol. 40, No. 5, January 2003)