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Linear Model Theory

With Examples and Exercises

저자
Dale L. Zimmerman
출판사
Springer International Publishing AG
출간
2021
쪽수
504쪽
언어
영어
ISBN
9783030520656
상태
수량
배송

해외에서 들여옵니다. 보통 2~3주, 지금 주문하시면 11월 17일에서 11월 24일 사이 도착 예상

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담아 두시면 24시간 안에 가격을 알려 드립니다. 가격을 보시고 결제하시면 됩니다.

Linear Model Theory: Exercises and Solutions - This book contains 296 exercises and solutions covering a wide variety of topics in linear model theory, including generalized inverses, estimability, best linear unbiased estimation and prediction, ANOVA, confidence intervals, simultaneous confidence intervals, hypothesis testing, and variance component estimation. The models covered include the Gauss-Markov and Aitken models, mixed and random effects models, and the general mixed linear model. Given its content, the book will be useful for students and instructors alike. Readers can also consult the companion textbook Linear Model Theory - With Examples and Exercises by the same author for the theory behind the exercises.

Linear Model Theory: With Examples and Exercises This textbook presents a unified and rigorous approach to best linear unbiased estimation and prediction of parameters and random quantities in linear models, as well as other theory upon which much of the statistical methodology associated with linear models is based. The single most unique feature of the book is that each major concept or result is illustrated with one or more concrete examples or special cases. Commonly used methodologies based on the theory are presented in methodological interludes scattered throughout the book, along with a wealth of exercises that will benefit students and instructors alike. Generalized inverses are used throughout, so that the model matrix and various other matrices are not required to have full rank. Considerably more emphasis is given to estimability, partitioned analyses of variance, constrained least squares, effects of model misspecification, and most especially prediction than in many other textbooks on linear models. This book is intended for master and PhD students with a basic understanding of statistical theory, matrix algebra and applied regression analysis, and for instructors of linear models courses. Solutions to the book's exercises are available in the companion volumeLinear Model Theory - Exercises and Solutions by the same author.

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