Author: Alvin C. Rencher Publisher: John Wiley & Sons ISBN: 0470192607 Category : Mathematics Languages : en Pages : 690
Book Description
The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features: New chapters on Bayesian linear models as well as random and mixed linear models Expanded discussion of two-way models with empty cells Additional sections on the geometry of least squares Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS® code for all numerical examples. Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance.
Author: G. Jay Kerns Publisher: Lulu.com ISBN: 0557249791 Category : Education Languages : en Pages : 388
Book Description
This is a textbook for an undergraduate course in probability and statistics. The approximate prerequisites are two or three semesters of calculus and some linear algebra. Students attending the class include mathematics, engineering, and computer science majors.
Author: Berl Kagan Publisher: KTAV Publishing House, Inc. ISBN: 9780881255805 Category : History Languages : en Pages : 454
Book Description
The story of the former Polish-Jewish community (shtetl) of Luboml, Wołyń, Poland. Its Jewish population of some 4,000, dating back to the 14th century, was exterminated by the occupying German forces and local collaborators in October, 1942. Luboml was formerly known as Lyuboml, Volhynia, Russia and later Lyuboml, Volyns'ka, Ukraine. It was also know by its Yiddish name: Libivne.
Author: Michael Kapovich Publisher: Springer Science & Business Media ISBN: 0817649131 Category : Mathematics Languages : en Pages : 486
Book Description
Hyperbolic Manifolds and Discrete Groups is at the crossroads of several branches of mathematics: hyperbolic geometry, discrete groups, 3-dimensional topology, geometric group theory, and complex analysis. The main focus throughout the text is on the "Big Monster," i.e., on Thurston’s hyperbolization theorem, which has not only completely changes the landscape of 3-dimensinal topology and Kleinian group theory but is one of the central results of 3-dimensional topology. The book is fairly self-contained, replete with beautiful illustrations, a rich set of examples of key concepts, numerous exercises, and an extensive bibliography and index. It should serve as an ideal graduate course/seminar text or as a comprehensive reference.
Author: C.A. Nienaber Publisher: Springer ISBN: 9789401060240 Category : Medical Languages : en Pages : 284
Book Description
This book is an up-to-date summary of all aspects of aortic disease, written by international experts in their fields, covering diagnostic concepts of all aortic diseases, the most modern therapeutic approaches in various aortic syndromes, the pathogenic origin and the most recent molecular and cellular findings that have revolutionized our present knowledge of aortic diseases. The reader will come to understand the aorta as a functional organ with a complex regulatory system rather than just a major arterial vessel, and will have a better understanding of the prognostic impact of various aortic syndromes, and of the most recent therapeutic concepts for chronic as well as acute aortic pathology. As a unique feature of this book, the aorta is placed in the center of systemic illnesses, such as atherosclerosis, diabetes, hypertension, infectious diseases and connective tissue disorders, storage diseases, trauma and toxic factors; this concept aims to attract the attention of both clinical specialties such as cardiology, radiology and cardiovascular surgery and adjacent areas like pathology and clinical genetics. The book portrays the aorta as an integral part of the cardiovascular system and the entire organism and features the complexity and clinical impact of all major aortic diseases.
Author: Mara Einstein Publisher: Routledge ISBN: 1134130104 Category : Business & Economics Languages : en Pages : 256
Book Description
Through a series of fascinating case studies of faith brands, marketing insider Mara Einstein has produced a lively account of the book in the commercialization of religion.
Author: Evarist Giné Publisher: Cambridge University Press ISBN: 1009022784 Category : Mathematics Languages : en Pages : 706
Book Description
In nonparametric and high-dimensional statistical models, the classical Gauss–Fisher–Le Cam theory of the optimality of maximum likelihood estimators and Bayesian posterior inference does not apply, and new foundations and ideas have been developed in the past several decades. This book gives a coherent account of the statistical theory in infinite-dimensional parameter spaces. The mathematical foundations include self-contained 'mini-courses' on the theory of Gaussian and empirical processes, approximation and wavelet theory, and the basic theory of function spaces. The theory of statistical inference in such models - hypothesis testing, estimation and confidence sets - is presented within the minimax paradigm of decision theory. This includes the basic theory of convolution kernel and projection estimation, but also Bayesian nonparametrics and nonparametric maximum likelihood estimation. In a final chapter the theory of adaptive inference in nonparametric models is developed, including Lepski's method, wavelet thresholding, and adaptive inference for self-similar functions. Winner of the 2017 PROSE Award for Mathematics.
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