Proceedings Of The International Conference On Trends And Perspectives In Linear Statistical Inference Linstat 2008
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International Conference on Trends and Perspectives in Linear Statistical Inference with Celebration of Tadeusz Caliński's 90th Birthday
| Author | : Katarzyna Filipiak |
| Publisher | : |
| Total Pages | : |
| Release | : 2018 |
| Genre | : |
| ISBN | : 9788379861965 |
Trends and Perspectives in Linear Statistical Inference
| Author | : Müjgan Tez |
| Publisher | : Springer |
| Total Pages | : 261 |
| Release | : 2018-02-01 |
| Genre | : Mathematics |
| ISBN | : 3319732412 |
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.
Statistical Tolerance Regions
| Author | : Kalimuthu Krishnamoorthy |
| Publisher | : John Wiley & Sons |
| Total Pages | : 494 |
| Release | : 2009-05-06 |
| Genre | : Mathematics |
| ISBN | : 0470473894 |
A modern and comprehensive treatment of tolerance intervals and regions The topic of tolerance intervals and tolerance regions has undergone significant growth during recent years, with applications arising in various areas such as quality control, industry, and environmental monitoring. Statistical Tolerance Regions presents the theoretical development of tolerance intervals and tolerance regions through computational algorithms and the illustration of numerous practical uses and examples. This is the first book of its kind to successfully balance theory and practice, providing a state-of-the-art treatment on tolerance intervals and tolerance regions. The book begins with the key definitions, concepts, and technical results that are essential for deriving tolerance intervals and tolerance regions. Subsequent chapters provide in-depth coverage of key topics including: Univariate normal distribution Non-normal distributions Univariate linear regression models Nonparametric tolerance intervals The one-way random model with balanced data The multivariate normal distribution The one-way random model with unbalanced data The multivariate linear regression model General mixed models Bayesian tolerance intervals A final chapter contains coverage of miscellaneous topics including tolerance limits for a ratio of normal random variables, sample size determination, reference limits and coverage intervals, tolerance intervals for binomial and Poisson distributions, and tolerance intervals based on censored samples. Theoretical explanations are accompanied by computational algorithms that can be easily replicated by readers, and each chapter contains exercise sets for reinforcement of the presented material. Detailed appendices provide additional data sets and extensive tables of univariate and multivariate tolerance factors. Statistical Tolerance Regions is an ideal book for courses on tolerance intervals at the graduate level. It is also a valuable reference and resource for applied statisticians, researchers, and practitioners in industry and pharmaceutical companies.
MODA4 — Advances in Model-Oriented Data Analysis
| Author | : Christos P. Kitsos |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 295 |
| Release | : 2013-06-29 |
| Genre | : Business & Economics |
| ISBN | : 3662125161 |
This volume is the proceedings of the 4th International Workshop on Model-Oriented Data Analysis. This series of events originated in 1987 at a meeting in Eisenach, that successfully brought together scientists from numerous countries of the 'East ' and 'West'. Now that this distinction is obsolete dialogue has been greatly facilitated, providing opportunities for this dialogue, however, is as vital as ever. The present meeting at Spetses, Greece from 5th to 9th of June 1995 again assembles statisticians from all over the world as this book documents. The hospitality offered by the University of Economics of Athens and the Korgialenios School made it possible to organize this workshop. The editors are also grateful to Intracom (Greece), the Ionian Bank and the Procter & Gamble Company (USA) for their generous support. We would particularly like to mention Dr. Michael Meredith, who being our contact person at Procter & Gamble, enabled us to publish these proceedings. Further thanks go to Dr. Peter Schuster from Physica Verlag Heidelberg for his continuing support of the project. The contributions to this volume were carefully selected from the submissions by the editors after a one stage refereeing process. We would like to thank the members of the MODA committee, A.C. Atkinson, R.D. Cook, V.V. Fedorov, P.Hackl, H. Lauter, B.Torsney, LN. Vuchkov, H.P.Wynn,and A.A. Zhigljavsky, who not only defined the main topics of the workshop, but also served as the referees.
Multivariate, Multilinear and Mixed Linear Models
| Author | : Katarzyna Filipiak |
| Publisher | : Springer Nature |
| Total Pages | : 357 |
| Release | : 2021-10-01 |
| Genre | : Mathematics |
| ISBN | : 3030754944 |
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.
Handbook of Regression Methods
| Author | : Derek Scott Young |
| Publisher | : CRC Press |
| Total Pages | : 654 |
| Release | : 2018-10-03 |
| Genre | : Mathematics |
| ISBN | : 1498775306 |
Handbook of Regression Methods concisely covers numerous traditional, contemporary, and nonstandard regression methods. The handbook provides a broad overview of regression models, diagnostic procedures, and inference procedures, with emphasis on how these methods are applied. The organization of the handbook benefits both practitioners and researchers, who seek either to obtain a quick understanding of regression methods for specialized problems or to expand their own breadth of knowledge of regression topics. This handbook covers classic material about simple linear regression and multiple linear regression, including assumptions, effective visualizations, and inference procedures. It presents an overview of advanced diagnostic tests, remedial strategies, and model selection procedures. Finally, many chapters are devoted to a diverse range of topics, including censored regression, nonlinear regression, generalized linear models, and semiparametric regression. Features Presents a concise overview of a wide range of regression topics not usually covered in a single text Includes over 80 examples using nearly 70 real datasets, with results obtained using R Offers a Shiny app containing all examples, thus allowing access to the source code and the ability to interact with the analyses
Statistical Data Analysis and Inference
| Author | : Y. Dodge |
| Publisher | : Elsevier |
| Total Pages | : 630 |
| Release | : 2014-05-23 |
| Genre | : Mathematics |
| ISBN | : 1483296113 |
A wide range of topics and perspectives in the field of statistics are brought together in this volume. The contributions originate from invited papers presented at an international conference which was held in honour of C. Radhakrishna Rao, one of the most eminent statisticians of our time and a distinguished scientist.
Regression Graphics
| Author | : R. Dennis Cook |
| Publisher | : John Wiley & Sons |
| Total Pages | : 378 |
| Release | : 2009-09-25 |
| Genre | : Mathematics |
| ISBN | : 0470317779 |
An exploration of regression graphics through computer graphics. Recent developments in computer technology have stimulated new and exciting uses for graphics in statistical analyses. Regression Graphics, one of the first graduate-level textbooks on the subject, demonstrates how statisticians, both theoretical and applied, can use these exciting innovations. After developing a relatively new regression context that requires few scope-limiting conditions, Regression Graphics guides readers through the process of analyzing regressions graphically and assessing and selecting models. This innovative reference makes use of a wide range of graphical tools, including 2D and 3D scatterplots, 3D binary response plots, and scatterplot matrices. Supplemented by a companion ftp site, it features numerous data sets and applied examples that are used to elucidate the theory. Other important features of this book include: * Extensive coverage of a relatively new regression context based on dimension-reduction subspaces and sufficient summary plots * Graphical regression, an iterative visualization process for constructing sufficient regression views * Graphics for regressions with a binary response * Graphics for model assessment, including residual plots * Net-effects plots for assessing predictor contributions * Graphics for predictor and response transformations * Inverse regression methods * Access to a Web site of supplemental plots, data sets, and 3D color displays. An ideal text for students in graduate-level courses on statistical analysis, Regression Graphics is also an excellent reference for professional statisticians.
