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In statistical analysis with large numbers of variables, the invariance approach is becoming increasingly popular and useful because of its ability and usefulness to derive better statistical procedures. In this book, multivariate statistical inference is presented through invariance.

Beginning with the historical background of probability theory, this thoroughly revised text examines all important aspects of mathematical probability - including random variables, probability distributions, characteristic and generating functions, stochatic convergence, and limit theorems - and provides an introduction to various types of statistical problems, covering the broad range of statistical inference.;Requiring a prerequisite in calculus for complete understanding of the topics discussed, the Second Edition contains new material on: univariate distributions; multivariate...