Get up-to-speed on the latest methods of multivariatestatisticsMultivariate statistical methods provide a powerful tool foranalyzing data when observations are taken over a period of time onthe same subject. With the advent of fast and efficient computersand the availability of computer packages such as S-plus and SAS,multivariate methods once too complex to tackle are now withinreach of most researchers and data analysts. With an emphasis oncomputing techniques in combination with a full understanding ofthe mathematics behind the methods, Methods of MultivariateStatistics offers an up-to-date account of multivariate methods.Focusing on the maximum likelihood method for estimation, testingof hypotheses, and "profile analysis," this book offerscomprehensive discussions of commonly encountered multivariate dataand also covers some practical and important problems lacking inother texts. These include:* Missing at-random observations* "Growth Curve Models" and multivariate one-sided tests applicablein pharmaceutical and medical trials* Bootstrap methods* Principal component method for predicting a multivariate responsevector* Outlier detection and handling inference when covariance issingularWith clear chapter introductions and numerous problem sets, Methodsof Multivariate Statistics meets every statistician's need for acomprehensive investigation of the latest methods in multivariatestatistics.