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Multivariate statistical inference
  • Language: en
  • Pages: 319

Multivariate statistical inference

  • Type: Book
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  • Published: 1977
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  • Publisher: Unknown

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Multivariate statistical inference and applications
  • Language: en
  • Pages: 559

Multivariate statistical inference and applications

The most accessible introduction to the theory and practice of multivariate analysis Multivariate Statistical Inference and Applications is a user-friendly introduction to basic multivariate analysis theory and practice for statistics majors as well as nonmajors with little or no background in theoretical statistics. Among the many special features of this extremely accessible first text on multivariate analysis are: * Clear, step-by-step explanations of all key concepts and procedures along with original, easy-to-follow proofs * Numerous problems, examples, and tables of distributions * Many real-world data sets drawn from a wide range of disciplines * Reviews of univariate procedures that ...

Multivariate analysis
  • Language: en
  • Pages: 587

Multivariate analysis

Structural Sensitivity in Econometric Models Edwin Kuh, John W. Neese and Peter Hollinger Provides a pathbreaking assessment of the worth of linear dynamic systems methods for probing the behavior of complex macroeconomic models. Representing a major improvement upon the standard "black box" approach to analyzing economic model structure, it introduces the powerful concept of parameter sensitivity analysis within a linear systems root/vector framework. The approach is illustrated with a good mediumsize econometric model (Michigan Quarterly Econometric Model of the United States). EISPACK, the Fortran code for computing characteristic roots and vectors has been upgraded and augmented by a mod...

Methods of Multivariate Analysis
  • Language: en
  • Pages: 800

Methods of Multivariate Analysis

Praise for the Second Edition "This book is a systematic, well-written, well-organized text on multivariate analysis packed with intuition and insight . . . There is much practical wisdom in this book that is hard to find elsewhere." —IIE Transactions Filled with new and timely content, Methods of Multivariate Analysis, Third Edition provides examples and exercises based on more than sixty real data sets from a wide variety of scientific fields. It takes a "methods" approach to the subject, placing an emphasis on how students and practitioners can employ multivariate analysis in real-life situations. This Third Edition continues to explore the key descriptive and inferential procedures tha...

An Introduction to Multivariate Statistical Analysis
  • Language: en
  • Pages: 675

An Introduction to Multivariate Statistical Analysis

  • Type: Book
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  • Published: 1984-09-28
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  • Publisher: Unknown

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....

The War Against the Family
  • Language: en
  • Pages: 655

The War Against the Family

  • Type: Book
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  • Published: 2007-08-01
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  • Publisher: BPS Books

Inspired by his own passionate experience as a son, husband, and father, Gairdner offers in this book a forum for a long-overdue debate about the future of the family in Western civilization.

Applied Multivariate Statistical Analysis
  • Language: en
  • Pages: 776

Applied Multivariate Statistical Analysis

  • Type: Book
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  • Published: 2013-07-24
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  • Publisher: Unknown

This market leader offers a readable introduction to the statistical analysis of multivariate observations. Gives readers the knowledge necessary to make proper interpretations and select appropriate techniques for analyzing multivariate data. Starts with a formulation of the population models, delineates the corresponding sample results, and liberally illustrates everything with examples. Offers an abundance of examples and exercises based on real data. Appropriate for experimental scientists in a variety of disciplines.

Operations and Production Systems with Multiple Objectives
  • Language: en
  • Pages: 1114

Operations and Production Systems with Multiple Objectives

The first comprehensive book to uniquely combine the three fields of systems engineering, operations/production systems, and multiple criteria decision making/optimization Systems engineering is the art and science of designing, engineering, and building complex systems—combining art, science, management, and engineering disciplines. Operations and Production Systems with Multiple Objectives covers all classical topics of operations and production systems as well as new topics not seen in any similiar textbooks before: small-scale design of cellular systems, large-scale design of complex systems, clustering, productivity and efficiency measurements, and energy systems. Filled with complete...

Multivariate Analysis
  • Language: en
  • Pages: 450

Multivariate Analysis

Combining a theoretical and data analytic approach to the subject of multivariate analysis, this revised edition emphasises contemporary developments in the field. Topics covered include econometrics, principal component analysis, factor analysis, canonical correlation analysis, discriminate analysis, cluster analysis, multi-dimensional scaling and directional data.

An Introduction to Generalized Linear Models, Third Edition
  • Language: en
  • Pages: 320

An Introduction to Generalized Linear Models, Third Edition

Continuing to emphasize numerical and graphical methods, An Introduction to Generalized Linear Models, Third Edition provides a cohesive framework for statistical modeling. This new edition of a bestseller has been updated with Stata, R, and WinBUGS code as well as three new chapters on Bayesian analysis. Like its predecessor, this edition presents the theoretical background of generalized linear models (GLMs) before focusing on methods for analyzing particular kinds of data. It covers normal, Poisson, and binomial distributions; linear regression models; classical estimation and model fitting methods; and frequentist methods of statistical inference. After forming this foundation, the authors explore multiple linear regression, analysis of variance (ANOVA), logistic regression, log-linear models, survival analysis, multilevel modeling, Bayesian models, and Markov chain Monte Carlo (MCMC) methods. Using popular statistical software programs, this concise and accessible text illustrates practical approaches to estimation, model fitting, and model comparisons. It includes examples and exercises with complete data sets for nearly all the models covered.