Multivariate Statistical Simulation Mark E. Johnson For the researcher in statistics, probability, and operations research involved in the design and execution of a computer–aided simulation study utilizing continuous multivariate distributions, this book considers the properties of such distributions from a unique perspective. With enhancing graphics (three–dimensional and contour plots), it presents generation algorithms revealing features of the distribution undisclosed in preliminary algebraic manipulations. Well–known multivariate distributions covered include normal mixtures, elliptically assymmetric, Johnson translation, Khintine, and Burr–Pareto–logistic. 1987 (0 471–82290–6) 230 pp. Aspects of Multivariate Statistical Theory Robb J. Muirhead A classical mathematical treatment of the techniques, distributions, and inferences based on the multivariate normal distributions. The main focus is on distribution theory�both exact and asymptotic. Introduces three main areas of current activity overlooked or inadequately covered in existing texts: noncentral distribution theory, decision theoretic estimation of the parameters of a multivariate normal distribution, and the uses of spherical and elliptical distributions in multivariate analysis. 1982 (0 471–09442–0) 673 pp. Multivariate Observations G. A. F. Seber This up–to–date, comprehensive sourcebook treats data–oriented techniques and classical methods. It concerns the external analysis of differences among objects, and the internal analysis of how the variables measured relate to one another within objects. The scope ranges from the practical problems of graphically representing high dimensional data to the theoretical problems relating to matrices of random variables. 1984 (0 471–88104–X) 686 pp.

About the Author

About the author Theodore W. Anderson is Professor of Statistics and Economics at Stanford University. He is the author of The Statistical Analysis of Time Series, A Bibliography of Multivariate Statistical Analysis, and An Introduction to the Statistical Analysis of Data. Dr. Anderson is a Fellow of the Institute of Mathematical Statistics, the American Statistical Association, the Royal Statistical Society, and the American Academy of Arts & Sciences. He is a member of the American Mathematical Society, the International Institute of Statistics, and the National Academy of Sciences. Dr. Anderson earned his PhD in mathematics at Princeton University.

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