Parameter Estimation And Hypothesis Testing In Linear Models
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Parameter Estimation And Hypothesis Testing In Linear Models
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Author : Karl-Rudolf Koch
language : en
Publisher: Springer Science & Business Media
Release Date : 2013-03-09
Parameter Estimation And Hypothesis Testing In Linear Models written by Karl-Rudolf Koch and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-03-09 with Mathematics categories.
The necessity to publish the second edition of this book arose when its third German edition had just been published. This second English edition is there fore a translation of the third German edition of Parameter Estimation and Hypothesis Testing in Linear Models, published in 1997. It differs from the first English edition by the addition of a new chapter on robust estimation of parameters and the deletion of the section on discriminant analysis, which has been more completely dealt with by the author in the book Bayesian In ference with Geodetic Applications, Springer-Verlag, Berlin Heidelberg New York, 1990. Smaller additions and deletions have been incorporated, to im prove the text, to point out new developments or to eliminate errors which became apparent. A few examples have been also added. I thank Springer-Verlag for publishing this second edition and for the assistance in checking the translation, although the responsibility of errors remains with the author. I also want to express my thanks to Mrs. Ingrid Wahl and to Mrs. Heidemarlen Westhiiuser who prepared the second edition. Bonn, January 1999 Karl-Rudolf Koch Preface to the First Edition This book is a translation with slight modifications and additions of the second German edition of Parameter Estimation and Hypothesis Testing in Linear Models, published in 1987.
Parameter Estimation And Hypothesis Testing In Linear Models
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Author : Karl-Rudolf Koch
language : en
Publisher: Springer Science & Business Media
Release Date : 1999-04
Parameter Estimation And Hypothesis Testing In Linear Models written by Karl-Rudolf Koch and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 1999-04 with Mathematics categories.
A treatment of estimating unknown parameters, testing hypotheses and estimating confidence intervals in linear models. Readers will find here presentations of the Gauss-Markoff model, the analysis of variance, the multivariate model, the model with unknown variance and covariance components and the regression model as well as the mixed model for estimating random parameters. A chapter on the robust estimation of parameters and several examples have been added to this second edition. The necessary theorems of vector and matrix algebra and the probability distributions of test statistics are derived so as to make this book self-contained. Geodesy students as well as those in the natural sciences and engineering will find the emphasis on the geodetic application of statistical models extremely useful.
Parameter Estimation And Hypothesis Testing In Linear Models
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Author : K.-r Koch
language : it
Publisher:
Release Date :
Parameter Estimation And Hypothesis Testing In Linear Models written by K.-r Koch and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.
Linear Models In Statistics
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Author : Alvin C. Rencher
language : en
Publisher: John Wiley & Sons
Release Date : 2008-01-07
Linear Models In Statistics written by Alvin C. Rencher and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-01-07 with Mathematics categories.
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.
Using R For Principles Of Econometrics
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Author : Constantin Colonescu
language : en
Publisher: Lulu.com
Release Date : 2017-12-28
Using R For Principles Of Econometrics written by Constantin Colonescu and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-12-28 with Business & Economics categories.
This is a beginner's guide to applied econometrics using the free statistics software R. It provides and explains R solutions to most of the examples in 'Principles of Econometrics' by Hill, Griffiths, and Lim, fourth edition. 'Using R for Principles of Econometrics' requires no previous knowledge in econometrics or R programming, but elementary notions of statistics are helpful.
The Conway Maxwell Poisson Distribution
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Author : Kimberly F. Sellers
language : en
Publisher: Cambridge University Press
Release Date : 2023-03-09
The Conway Maxwell Poisson Distribution written by Kimberly F. Sellers and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-09 with Mathematics categories.
This is the first comprehensive introduction to the Conway-Maxwell-Poisson distribution and its contributions in statistical theory and computing in R, including its uses in count data modelling. An essential reference for academics in statistics and data science, as well as quantitative researchers and data analysts in applied disciplines.
Meta Analysis Of Controlled Clinical Trials
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Author : Anne Whitehead
language : en
Publisher: John Wiley & Sons
Release Date : 2002-08-16
Meta Analysis Of Controlled Clinical Trials written by Anne Whitehead and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2002-08-16 with Mathematics categories.
Over the last twenty years there has been a dramatic upsurge in the application of meta-analysis to medical research. This has mainly been due to greater emphasis on evidence-based medicine and the need for reliable summaries of the vast and expanding volume of clinical research. At the same time there have been great strides in the development and refinement of the associated statistical methodology. This book describes the planning, conduct and reporting of a meta-analysis as applied to a series of randomized controlled clinical trials. The various approaches are presented within a general unified framework. Meta-analysis techniques are described in detail, from their theoretical development through to practical implementation. Each topic discussed is supported by detailed worked examples. A comparison of fixed and random effects approaches is included, as well as a discussion of Bayesian methods and cumulative meta-analysis. Fully documented programs using standard statistical procedures in SAS are available on the Web. Ideally suited for practising statisticians and statistically-minded medical professionals, the book will also be of use to graduate students of medical statistics. The book is a self-contained and comprehensive account of the subject and an essential purchase for anyone involved in clinical trials.
Applied Multivariate Statistical Analysis In Medicine
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Author : Jingmei Jiang
language : en
Publisher: Elsevier
Release Date : 2024-08-21
Applied Multivariate Statistical Analysis In Medicine written by Jingmei Jiang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-21 with Science categories.
Applied Multivariate Statistical Analysis in Medicine provides a multivariate conceptual framework that allows readers to understand the interconnectivity and interrelations among variables, which maintains the intrinsic precision of statistical theories. With a strong focus on the fundamental concepts of multivariate statistical analysis, the book also gives insight into the applications of multivariate distribution in biomedical fields. In 14 chapters, Applied Multivariate Statistical Analysis in Medicine covers the main topics of multivariate analysis methods widely used in health science research. The content is organized progressively from fundamental concepts to sophisticated methods. It begins with basic descriptive statistics in multivariate analysis and follows with parameter estimation, in addition to the hypothesis testing of a multivariate normal distribution, which has heavy applications in biomedical fields where the relationships among approximately normal variables are of great interest. Keeping mathematics to a minimum, considerable emphasis is placed on explanations and real-world applications of core principles to maintain a good balance between introducing theory and cultivating problem-solving skills. This book is a very valuable reference text for clinicians, medical researchers, and other researchers across medical and biomedical disciplines, all of whom confront increasingly complex statistical methods during the analysis and presentation of their results. - Gives understanding and mastering of the multivariate analysis techniques in the medical sciences - Maintains a balance between the introduction of statistical analysis theory and the cultivation of practical skills - Exposes a variety of well-designed real-life cases that integrate concepts and analytical techniques - Includes substantive exercises, online coding sources, and case discussions to solidify a conceptual understanding
Foundational And Applied Statistics For Biologists Using R
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Author : Ken A. Aho
language : en
Publisher: CRC Press
Release Date : 2016-03-09
Foundational And Applied Statistics For Biologists Using R written by Ken A. Aho and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-03-09 with Mathematics categories.
Full of biological applications, exercises, and interactive graphical examples, this text presents comprehensive coverage of both modern analytical methods and statistical foundations. The author harnesses the inherent properties of the R environment to enable students to examine the code of complicated procedures step by step and thus better understand the process of obtaining analysis results. The graphical capabilities of R are used to provide interactive demonstrations of simple to complex statistical concepts. R code and other materials are available online.
Simposio Internacional De Estadistica En Agricultura Y Medio Ambiente
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Author :
language : en
Publisher: CIAT
Release Date :
Simposio Internacional De Estadistica En Agricultura Y Medio Ambiente written by and has been published by CIAT this book supported file pdf, txt, epub, kindle and other format this book has been release on with categories.