Linear Regression Techniques For Identifying Influential Data And Applications In Commercial Data Analysis

Linear Regression Techniques for Identifying Influential Data and Applications in Commercial Data Analysis

Methods for Statistical Data Analysis of Multivariate Observations

A practical guide for multivariate statistical techniques-- nowupdated and revised In recent years, innovations in computer technology and statisticalmethodologies have dramatically altered the landscape ofmultivariate data analysis. This new edition of Methods forStatistical Data Analysis of Multivariate Observations explorescurrent multivariate concepts and techniques while retaining thesame practical focus of its predecessor. It integrates methods anddata-based interpretations relevant to multivariate analysis in away that addresses real-world problems arising in many areas ofinterest. Greatly revised and updated, this Second Edition provides helpfulexamples, graphical orientation, numerous illustrations, and anappendix detailing statistical software, including the S (or Splus)and SAS systems. It also offers * An expanded chapter on cluster analysis that covers advances inpattern recognition * New sections on inputs to clustering algorithms and aids forinterpreting the results of cluster analysis * An exploration of some new techniques of summarization andexposure * New graphical methods for assessing the separations among theeigenvalues of a correlation matrix and for comparing sets ofeigenvectors * Knowledge gained from advances in robust estimation anddistributional models that are slightly broader than themultivariate normal This Second Edition is invaluable for graduate students, appliedstatisticians, engineers, and scientists wishing to usemultivariate techniques in a variety of disciplines.

Probability

The brand new edition of this classic text--with more exercises andeasier to use than ever Like the first edition, this new version ofLamperti's classic text succeeds in making this fascinating area ofmathematics accessible to readers who have limited knowledge ofmeasure theory and only some familiarity with elementaryprobability. Streamlined for even greater clarity and with moreexercises to help develop and reinforce skills, Probability isideal for graduate and advanced undergraduate students--both in andout of the classroom. Probability covers: * Probability spaces, random variables, and other fundamentalconcepts * Laws of large numbers and random series, including the Law of theIterated Logarithm * Characteristic functions, limiting distributions for sums andmaxima, and the "Central Limit Problem" * The Brownian Motion process