The Coordinate Free Approach To Linear Models

Download The Coordinate Free Approach To Linear Models full books in PDF, epub, and Kindle. Read online The Coordinate Free Approach To Linear Models ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

The Coordinate-Free Approach to Linear Models

Author : Michael J. Wichura
Publisher : Cambridge University Press
ISBN 13 : 1139461044
Total Pages : 188 pages
Book Rating : 4.1/5 (394 download)

DOWNLOAD NOW!

Book Synopsis The Coordinate-Free Approach to Linear Models by : Michael J. Wichura

Download or read book The Coordinate-Free Approach to Linear Models written by Michael J. Wichura and published by Cambridge University Press. This book was released on 2006-10-23 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is about the coordinate-free, or geometric, approach to the theory of linear models; more precisely, Model I ANOVA and linear regression models with non-random predictors in a finite-dimensional setting. This approach is more insightful, more elegant, more direct, and simpler than the more common matrix approach to linear regression, analysis of variance, and analysis of covariance models in statistics. The book discusses the intuition behind and optimal properties of various methods of estimating and testing hypotheses about unknown parameters in the models. Topics covered range from linear algebra, such as inner product spaces, orthogonal projections, book orthogonal spaces, Tjur experimental designs, basic distribution theory, the geometric version of the Gauss-Markov theorem, optimal and non-optimal properties of Gauss-Markov, Bayes, and shrinkage estimators under assumption of normality, the optimal properties of F-test, and the analysis of covariance and missing observations.

Lecture Notes on the Coordinate-free Approach to Linear Models

Author : Michael J. Wichura
Publisher :
ISBN 13 :
Total Pages : 260 pages
Book Rating : 4.E/5 ( download)

DOWNLOAD NOW!

Book Synopsis Lecture Notes on the Coordinate-free Approach to Linear Models by : Michael J. Wichura

Download or read book Lecture Notes on the Coordinate-free Approach to Linear Models written by Michael J. Wichura and published by . This book was released on 1983 with total page 260 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Plane Answers to Complex Questions

Author : Ronald Christensen
Publisher : Springer Nature
ISBN 13 : 3030320979
Total Pages : 539 pages
Book Rating : 4.0/5 (33 download)

DOWNLOAD NOW!

Book Synopsis Plane Answers to Complex Questions by : Ronald Christensen

Download or read book Plane Answers to Complex Questions written by Ronald Christensen and published by Springer Nature. This book was released on 2020-03-13 with total page 539 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a wide-ranging introduction to the use and theory of linear models for analyzing data. The author's emphasis is on providing a unified treatment of linear models, including analysis of variance models and regression models, based on projections, orthogonality, and other vector space ideas. Every chapter comes with numerous exercises and examples that make it ideal for a graduate-level course. All of the standard topics are covered in depth: estimation including biased and Bayesian estimation, significance testing, ANOVA, multiple comparisons, regression analysis, and experimental design models. In addition, the book covers topics that are not usually treated at this level, but which are important in their own right: best linear and best linear unbiased prediction, split plot models, balanced incomplete block designs, testing for lack of fit, testing for independence, models with singular covariance matrices, diagnostics, collinearity, and variable selection. This new edition includes new sections on alternatives to least squares estimation and the variance-bias tradeoff, expanded discussion of variable selection, new material on characterizing the interaction space in an unbalanced two-way ANOVA, Freedman's critique of the sandwich estimator, and much more.

Methodology and Applications of Statistics

Author : Barry C. Arnold
Publisher : Springer Nature
ISBN 13 : 3030836703
Total Pages : 447 pages
Book Rating : 4.0/5 (38 download)

DOWNLOAD NOW!

Book Synopsis Methodology and Applications of Statistics by : Barry C. Arnold

Download or read book Methodology and Applications of Statistics written by Barry C. Arnold and published by Springer Nature. This book was released on 2022-01-04 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dedicated to one of the most outstanding researchers in the field of statistics, this volume in honor of C.R. Rao, on the occasion of his 100th birthday, provides a bird’s-eye view of a broad spectrum of research topics, paralleling C.R. Rao’s wide-ranging research interests. The book’s contributors comprise a representative sample of the countless number of researchers whose careers have been influenced by C.R. Rao, through his work or his personal aid and advice. As such, written by experts from more than 15 countries, the book’s original and review contributions address topics including statistical inference, distribution theory, estimation theory, multivariate analysis, hypothesis testing, statistical modeling, design and sampling, shape and circular analysis, and applications. The book will appeal to statistics researchers, theoretical and applied alike, and PhD students. Happy Birthday, C.R. Rao!

The Coordinate-Free Approach to Gauss-Markov Estimation

Author : H. Drygas
Publisher : Springer Science & Business Media
ISBN 13 : 3642651488
Total Pages : 125 pages
Book Rating : 4.6/5 (426 download)

DOWNLOAD NOW!

Book Synopsis The Coordinate-Free Approach to Gauss-Markov Estimation by : H. Drygas

Download or read book The Coordinate-Free Approach to Gauss-Markov Estimation written by H. Drygas and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: These notes originate from a couple of lectures which were given in the Econometric Workshop of the Center for Operations Research and Econometrics (CORE) at the Catholic University of Louvain. The participants of the seminars were recommended to read the first four chapters of Seber's book [40], but the exposition of the material went beyond Seber's exposition, if it seemed necessary. Coordinate-free methods are not new in Gauss-Markov estimation, besides Seber the work of Kolmogorov [11], SCheffe [36], Kruskal [21], [22] and Malinvaud [25], [26] should be mentioned. Malinvaud's approach however is a little different from that of the other authors, because his optimality criterion is based on the ellipsoid of c- centration. This criterion is however equivalent to the usual c- cept of minimal covariance-matrix and therefore the result must be the same in both cases. While the usual theory gives no indication how small the covariance-matrix can be made before the optimal es timator is computed, Malinvaud can show how small the ellipsoid of concentration can be made: it is at most equal to the intersection of the ellipssoid of concentration of the observed random vector and the linear space in which the (unknown) expectation value of the observed random vector is lying. This exposition is based on the observation, that in regression ~nalysis and related fields two conclusions are or should preferably be applied repeatedly.

Linear Models: An Integrated Approach

Author : S Rao Jammalamadaka
Publisher : World Scientific
ISBN 13 : 9814491268
Total Pages : 646 pages
Book Rating : 4.8/5 (144 download)

DOWNLOAD NOW!

Book Synopsis Linear Models: An Integrated Approach by : S Rao Jammalamadaka

Download or read book Linear Models: An Integrated Approach written by S Rao Jammalamadaka and published by World Scientific. This book was released on 2003-03-03 with total page 646 pages. Available in PDF, EPUB and Kindle. Book excerpt: Linear Models: An Integrated Approach aims to provide a clear and deep understanding of the general linear model using simple statistical ideas. Elegant geometric arguments are also invoked as needed and a review of vector spaces and matrices is provided to make the treatment self-contained. Complex, matrix-algebraic methods, such as those used in the rank-deficient case, are replaced by statistical proofs that are more transparent and that show the parallels with the simple linear model.This book has the following special features:

Linear Models in Statistics

Author : Alvin C. Rencher
Publisher : John Wiley & Sons
ISBN 13 : 0470192607
Total Pages : 690 pages
Book Rating : 4.4/5 (71 download)

DOWNLOAD NOW!

Book Synopsis Linear Models in Statistics by : Alvin C. Rencher

Download or read book Linear Models in Statistics written by Alvin C. Rencher and published by John Wiley & Sons. This book was released on 2008-01-07 with total page 690 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Linear Model Methodology

Author : Andre I. Khuri
Publisher : CRC Press
ISBN 13 : 1420010441
Total Pages : 562 pages
Book Rating : 4.4/5 (2 download)

DOWNLOAD NOW!

Book Synopsis Linear Model Methodology by : Andre I. Khuri

Download or read book Linear Model Methodology written by Andre I. Khuri and published by CRC Press. This book was released on 2009-10-21 with total page 562 pages. Available in PDF, EPUB and Kindle. Book excerpt: Given the importance of linear models in statistical theory and experimental research, a good understanding of their fundamental principles and theory is essential. Supported by a large number of examples, Linear Model Methodology provides a strong foundation in the theory of linear models and explores the latest developments in data analysis.After

Bilinear Regression Analysis

Author : Dietrich von Rosen
Publisher : Springer
ISBN 13 : 3319787845
Total Pages : 473 pages
Book Rating : 4.3/5 (197 download)

DOWNLOAD NOW!

Book Synopsis Bilinear Regression Analysis by : Dietrich von Rosen

Download or read book Bilinear Regression Analysis written by Dietrich von Rosen and published by Springer. This book was released on 2018-08-02 with total page 473 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book expands on the classical statistical multivariate analysis theory by focusing on bilinear regression models, a class of models comprising the classical growth curve model and its extensions. In order to analyze the bilinear regression models in an interpretable way, concepts from linear models are extended and applied to tensor spaces. Further, the book considers decompositions of tensor products into natural subspaces, and addresses maximum likelihood estimation, residual analysis, influential observation analysis and testing hypotheses, where properties of estimators such as moments, asymptotic distributions or approximations of distributions are also studied. Throughout the text, examples and several analyzed data sets illustrate the different approaches, and fresh insights into classical multivariate analysis are provided. This monograph is of interest to researchers and Ph.D. students in mathematical statistics, signal processing and other fields where statistical multivariate analysis is utilized. It can also be used as a text for second graduate-level courses on multivariate analysis.

Models for Discreet Data

Author : Daniel Zelterman
Publisher : Oxford University Press, USA
ISBN 13 : 0191523437
Total Pages : 297 pages
Book Rating : 4.1/5 (915 download)

DOWNLOAD NOW!

Book Synopsis Models for Discreet Data by : Daniel Zelterman

Download or read book Models for Discreet Data written by Daniel Zelterman and published by Oxford University Press, USA. This book was released on 1999-01-21 with total page 297 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discrete or count data arise in experiments where the outcome variables are the numbers of individuals classified into unique, non-overlapping categories. This revised edition describes the statistical models used in the analysis and summary of such data, and provides a sound introduction to the subject for graduate students and practitioners needing a review of the methodology. With many numerical examples throughout, it includes topics not covered in depth elsewhere, such as thenegative multinomial distribution; the many forms of the hypergeometric distribution; and coordinate free models. A detailed treatment of sample size estimation and power are given in terms of both exact inference and asymptotic, non-central chi-squared methods. A new section covering Poissonregression has also been included. An important feature of this book, missing elsewhere, is the integration of the software into the text.Many more exercises are provided (including 84% more applied exercises) than in the previous edition, helping consolidate the reader's understanding of all subjects covered, and making the book highly suitable for use in a classroom setting. Several new datasets, mostly from the health and medical sector, are discussed, including previously unpublished data from a study of Tourette's Syndrome in children.

Multivariate, Multilinear and Mixed Linear Models

Author : Katarzyna Filipiak
Publisher : Springer Nature
ISBN 13 : 3030754944
Total Pages : 357 pages
Book Rating : 4.0/5 (37 download)

DOWNLOAD NOW!

Book Synopsis Multivariate, Multilinear and Mixed Linear Models by : Katarzyna Filipiak

Download or read book Multivariate, Multilinear and Mixed Linear Models written by Katarzyna Filipiak and published by Springer Nature. This book was released on 2021-10-01 with total page 357 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest findings on statistical inference in multivariate, multilinear and mixed linear models, providing a holistic presentation of the subject. It contains pioneering and carefully selected review contributions by experts in the field and guides the reader through topics related to estimation and testing of multivariate and mixed linear model parameters. Starting with the theory of multivariate distributions, covering identification and testing of covariance structures and means under various multivariate models, it goes on to discuss estimation in mixed linear models and their transformations. The results presented originate from the work of the research group Multivariate and Mixed Linear Models and their meetings held at the Mathematical Research and Conference Center in Będlewo, Poland, over the last 10 years. Featuring an extensive bibliography of related publications, the book is intended for PhD students and researchers in modern statistical science who are interested in multivariate and mixed linear models.

Data Analysis and Graphics Using R

Author : John Maindonald
Publisher : Cambridge University Press
ISBN 13 : 1139486675
Total Pages : 565 pages
Book Rating : 4.1/5 (394 download)

DOWNLOAD NOW!

Book Synopsis Data Analysis and Graphics Using R by : John Maindonald

Download or read book Data Analysis and Graphics Using R written by John Maindonald and published by Cambridge University Press. This book was released on 2010-05-06 with total page 565 pages. Available in PDF, EPUB and Kindle. Book excerpt: Discover what you can do with R! Introducing the R system, covering standard regression methods, then tackling more advanced topics, this book guides users through the practical, powerful tools that the R system provides. The emphasis is on hands-on analysis, graphical display, and interpretation of data. The many worked examples, from real-world research, are accompanied by commentary on what is done and why. The companion website has code and datasets, allowing readers to reproduce all analyses, along with solutions to selected exercises and updates. Assuming basic statistical knowledge and some experience with data analysis (but not R), the book is ideal for research scientists, final-year undergraduate or graduate-level students of applied statistics, and practising statisticians. It is both for learning and for reference. This third edition expands upon topics such as Bayesian inference for regression, errors in variables, generalized linear mixed models, and random forests.

Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability

Author : Jerzy Neyman
Publisher : Univ of California Press
ISBN 13 :
Total Pages : 784 pages
Book Rating : 4./5 ( download)

DOWNLOAD NOW!

Book Synopsis Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability by : Jerzy Neyman

Download or read book Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability written by Jerzy Neyman and published by Univ of California Press. This book was released on 1961 with total page 784 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Plane Answers to Complex Questions

Author : Ronald Christensen
Publisher : Springer Science & Business Media
ISBN 13 :
Total Pages : 480 pages
Book Rating : 4.3/5 (91 download)

DOWNLOAD NOW!

Book Synopsis Plane Answers to Complex Questions by : Ronald Christensen

Download or read book Plane Answers to Complex Questions written by Ronald Christensen and published by Springer Science & Business Media. This book was released on 1996 with total page 480 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook provides a wide-ranging introduction to the use of linear models in analyzing data. The author's emphasis is on providing a unified treatment of the analysis of variance models and regression models by presenting a vector space and projections approach to the subject. Every chapter comes with numerous exercises and examples, which will make it ideal for a graduate-level course on this subject.

Trends and Perspectives in Linear Statistical Inference

Author : Müjgan Tez
Publisher : Springer
ISBN 13 : 3319732412
Total Pages : 261 pages
Book Rating : 4.3/5 (197 download)

DOWNLOAD NOW!

Book Synopsis Trends and Perspectives in Linear Statistical Inference by : Müjgan Tez

Download or read book Trends and Perspectives in Linear Statistical Inference written by Müjgan Tez and published by Springer. This book was released on 2018-02-01 with total page 261 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume features selected contributions on a variety of topics related to linear statistical inference. The peer-reviewed papers from the International Conference on Trends and Perspectives in Linear Statistical Inference (LinStat 2016) held in Istanbul, Turkey, 22-25 August 2016, cover topics in both theoretical and applied statistics, such as linear models, high-dimensional statistics, computational statistics, the design of experiments, and multivariate analysis. The book is intended for statisticians, Ph.D. students, and professionals who are interested in statistical inference.

Mathematical Foundations of Infinite-Dimensional Statistical Models

Author : Evarist Giné
Publisher : Cambridge University Press
ISBN 13 : 1009022784
Total Pages : 706 pages
Book Rating : 4.0/5 (9 download)

DOWNLOAD NOW!

Book Synopsis Mathematical Foundations of Infinite-Dimensional Statistical Models by : Evarist Giné

Download or read book Mathematical Foundations of Infinite-Dimensional Statistical Models written by Evarist Giné and published by Cambridge University Press. This book was released on 2021-03-25 with total page 706 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Regression for Categorical Data

Author : Gerhard Tutz
Publisher : Cambridge University Press
ISBN 13 : 1139499580
Total Pages : 573 pages
Book Rating : 4.1/5 (394 download)

DOWNLOAD NOW!

Book Synopsis Regression for Categorical Data by : Gerhard Tutz

Download or read book Regression for Categorical Data written by Gerhard Tutz and published by Cambridge University Press. This book was released on 2011-11-21 with total page 573 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book introduces basic and advanced concepts of categorical regression with a focus on the structuring constituents of regression, including regularization techniques to structure predictors. In addition to standard methods such as the logit and probit model and extensions to multivariate settings, the author presents more recent developments in flexible and high-dimensional regression, which allow weakening of assumptions on the structuring of the predictor and yield fits that are closer to the data. A generalized linear model is used as a unifying framework whenever possible in particular parametric models that are treated within this framework. Many topics not normally included in books on categorical data analysis are treated here, such as nonparametric regression; selection of predictors by regularized estimation procedures; ternative models like the hurdle model and zero-inflated regression models for count data; and non-standard tree-based ensemble methods. The book is accompanied by an R package that contains data sets and code for all the examples.