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Reference - Linear Models and the Relevant Distributions and Matrix Algebra (Chapman & Hall/CRC Texts in Statistical Science)

Description

Book Synopsis: Linear Models and the Relevant Distributions and Matrix Algebra provides in-depth and detailed coverage of the use of linear statistical models as a basis for parametric and predictive inference. It can be a valuable reference, a primary or secondary text in a graduate-level course on linear models, or a resource used (in a course on mathematical statistics) to illustrate various theoretical concepts in the context of a relatively complex setting of great practical importance. Features:
  • Provides coverage of matrix algebra that is extensive and relatively self-contained and does so in a meaningful context
  • Provides thorough coverage of the relevant statistical distributions, including spherically and elliptically symmetric distributions
  • Includes extensive coverage of multiple-comparison procedures (and of simultaneous confidence intervals), including procedures for controlling the k-FWER and the FDR
  • Provides thorough coverage (complete with detailed and highly accessible proofs) of results on the properties of various linear-model procedures, including those of least squares estimators and those of the F test.
  • Features the use of real data sets for illustrative purposes
Includes many exercises David Harville served for 10 years as a mathematical statistician in the Applied Mathematics Research Laboratory of the Aerospace Research Laboratories at Wright-Patterson AFB, Ohio, 20 years as a full professor in Iowa State University’s Department of Statistics where he now has emeritus status, and seven years as a research staff member of the Mathematical Sciences Department of IBM’s T.J. Watson Research Center. He has considerable relevant experience, having taught M.S. and Ph.D. level courses in linear models, been the thesis advisor of 10 Ph.D. graduates, and authored or co-authored two books and more than 80 research articles. His work has been recognized through his election as a Fellow of the American Statistical Association and of the Institute of Mathematical Statistics and as a member of the International Statistical Institute.

Details

Are you looking to expand your knowledge of linear statistical models? Look no further! Linear Models and the Relevant Distributions and Matrix Algebra is the ultimate resource for anyone seeking in-depth understanding and coverage of linear models. Whether you're a graduate student in need of a comprehensive textbook or a professional wanting to strengthen your statistical skills, this book is sure to meet your needs.

One of the standout features of this book is its extensive coverage of matrix algebra. Not only is this coverage comprehensive, but it is also self-contained, meaning you can dive right into the material without needing prior knowledge. The book takes a meaningful approach by providing a context for the use of matrix algebra in statistical models, allowing you to understand how it applies to real-world scenarios.

Another key aspect of this book is its thorough coverage of relevant statistical distributions. From spherically and elliptically symmetric distributions to multiple-comparison procedures, you'll gain a comprehensive understanding of the distributions essential in statistical analysis. The book even delves into controlling the k-FWER and the FDR, giving you the tools to make accurate and confident interpretations of your data.

What truly sets this book apart is its practicality. It includes the use of real data sets, allowing you to see the concepts in action and apply them to your own research or professional work. The inclusion of detailed and highly accessible proofs ensures you have a solid foundation in the properties of various linear-model procedures, including least squares estimators and the F test.

Don't miss out on this invaluable resource! Written by David Harville, an esteemed mathematician and experienced instructor, this book is the product of years of dedicated research and teaching. Harville's expertise shines through in the comprehensive content, making this book a must-have for anyone seeking to enhance their understanding of linear models and statistical analysis.

Take your statistical knowledge to new heights with Linear Models and the Relevant Distributions and Matrix Algebra. Whether you're a student, researcher, or professional, this book will be an indispensable addition to your library. Don't wait, purchase now and unlock a world of statistical understanding!

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