Probability Models And Statistical Analyses For Ranking Data PDF Download
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| Author | : Michael A. Fligner |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 330 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 1461227380 |
Download Probability Models and Statistical Analyses for Ranking Data Book in PDF, ePub and Kindle
In June of 1990, a conference was held on Probablity Models and Statisti cal Analyses for Ranking Data, under the joint auspices of the American Mathematical Society, the Institute for Mathematical Statistics, and the Society of Industrial and Applied Mathematicians. The conference took place at the University of Massachusetts, Amherst, and was attended by 36 participants, including statisticians, mathematicians, psychologists and sociologists from the United States, Canada, Israel, Italy, and The Nether lands. There were 18 presentations on a wide variety of topics involving ranking data. This volume is a collection of 14 of these presentations, as well as 5 miscellaneous papers that were contributed by conference participants. We would like to thank Carole Kohanski, summer program coordinator for the American Mathematical Society, for her assistance in arranging the conference; M. Steigerwald for preparing the manuscripts for publication; Martin Gilchrist at Springer-Verlag for editorial advice; and Persi Diaconis for contributing the Foreword. Special thanks go to the anonymous referees for their careful readings and constructive comments. Finally, we thank the National Science Foundation for their sponsorship of the AMS-IMS-SIAM Joint Summer Programs. Contents Preface vii Conference Participants xiii Foreword xvii 1 Ranking Models with Item Covariates 1 D. E. Critchlow and M. A. Fligner 1. 1 Introduction. . . . . . . . . . . . . . . 1 1. 2 Basic Ranking Models and Their Parameters 2 1. 3 Ranking Models with Covariates 8 1. 4 Estimation 9 1. 5 Example. 11 1. 6 Discussion. 14 1. 7 Appendix . 15 1. 8 References.
| Author | : John I Marden |
| Publisher | : CRC Press |
| Total Pages | : 345 |
| Release | : 2014-01-23 |
| Genre | : Mathematics |
| ISBN | : 148225249X |
Download Analyzing and Modeling Rank Data Book in PDF, ePub and Kindle
This book is the first single source volume to fully address this prevalent practice in both its analytical and modeling aspects. The information discussed presents the use of data consisting of rankings in such diverse fields as psychology, animal science, educational testing, sociology, economics, and biology. This book systematically presents th
| Author | : Mayer Alvo |
| Publisher | : Springer |
| Total Pages | : 276 |
| Release | : 2014-09-02 |
| Genre | : Mathematics |
| ISBN | : 1493914715 |
Download Statistical Methods for Ranking Data Book in PDF, ePub and Kindle
This book introduces advanced undergraduate, graduate students and practitioners to statistical methods for ranking data. An important aspect of nonparametric statistics is oriented towards the use of ranking data. Rank correlation is defined through the notion of distance functions and the notion of compatibility is introduced to deal with incomplete data. Ranking data are also modeled using a variety of modern tools such as CART, MCMC, EM algorithm and factor analysis. This book deals with statistical methods used for analyzing such data and provides a novel and unifying approach for hypotheses testing. The techniques described in the book are illustrated with examples and the statistical software is provided on the authors’ website.
| Author | : John D. Kalbfleisch |
| Publisher | : John Wiley & Sons |
| Total Pages | : 462 |
| Release | : 2011-01-25 |
| Genre | : Mathematics |
| ISBN | : 1118031237 |
Download The Statistical Analysis of Failure Time Data Book in PDF, ePub and Kindle
Contains additional discussion and examples on left truncationas well as material on more general censoring and truncationpatterns. Introduces the martingale and counting process formulation swillbe in a new chapter. Develops multivariate failure time data in a separate chapterand extends the material on Markov and semi Markovformulations. Presents new examples and applications of data analysis.
| Author | : Chris J. Lloyd |
| Publisher | : Wiley-Interscience |
| Total Pages | : 496 |
| Release | : 1999-03-29 |
| Genre | : Mathematics |
| ISBN | : |
Download Statistical Analysis of Categorical Data Book in PDF, ePub and Kindle
Accessible, up-to-date coverage of a broad range of modern and traditional methods. The ability to understand and analyze categorical, or count, data is crucial to the success of statisticians in a wide variety of fields, including biomedicine, ecology, the social sciences, marketing, and many more. Statistical Analysis of Categorical Data provides thorough, clear, up-to-date explanations of all important methods of categorical data analysis at a level accessible to anyone with a solid undergraduate knowledge of statistics. Featuring a liberal use of real-world examples as well as a regression-based approach familiar to most students, this book reviews pertinent statistical theory, including advanced topics such as Score statistics and the transformed central limit theorem. It presents the distribution theory of Poisson as well as multinomial variables, and it points out the connections between them. Complete with numerous illustrations and exercises, this book covers the full range of topics necessary to develop a well-rounded understanding of modern categorical data analysis, including: * Logistic regression and log-linear models. * Exact conditional methods. * Generalized linear and additive models. * Smoothing count data with practical implementations in S-plus software. * Thorough description and analysis of five important computer packages. Supported by an ftp site, which describes the facilities important to a statistician wanting to analyze and report on categorical data, Statistical Analysis of Categorical Data is an excellent resource for students, practicing statisticians, and researchers with a special interest in count data.
| Author | : Hakan Andersson |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 140 |
| Release | : 2012-12-06 |
| Genre | : Mathematics |
| ISBN | : 1461211581 |
Download Stochastic Epidemic Models and Their Statistical Analysis Book in PDF, ePub and Kindle
The present lecture notes describe stochastic epidemic models and methods for their statistical analysis. Our aim is to present ideas for such models, and methods for their analysis; along the way we make practical use of several probabilistic and statistical techniques. This will be done without focusing on any specific disease, and instead rigorously analyzing rather simple models. The reader of these lecture notes could thus have a two-fold purpose in mind: to learn about epidemic models and their statistical analysis, and/or to learn and apply techniques in probability and statistics. The lecture notes require an early graduate level knowledge of probability and They introduce several techniques which might be new to students, but our statistics. intention is to present these keeping the technical level at a minlmum. Techniques that are explained and applied in the lecture notes are, for example: coupling, diffusion approximation, random graphs, likelihood theory for counting processes, martingales, the EM-algorithm and MCMC methods. The aim is to introduce and apply these techniques, thus hopefully motivating their further theoretical treatment. A few sections, mainly in Chapter 5, assume some knowledge of weak convergence; we hope that readers not familiar with this theory can understand the these parts at a heuristic level. The text is divided into two distinct but related parts: modelling and estimation.
| Author | : Marlos A. G. Viana |
| Publisher | : American Mathematical Soc. |
| Total Pages | : 354 |
| Release | : 2001 |
| Genre | : Mathematics |
| ISBN | : 0821826875 |
Download Algebraic Methods in Statistics and Probability Book in PDF, ePub and Kindle
The 23 papers report recent developments in using the technique to help clarify the relationship between phenomena and data in a number of natural and social sciences. Among the topics are a coordinate-free approach to multivariate exponential families, some rank-based hypothesis tests for covariance structure and conditional independence, deconvolution density estimation on compact Lie groups, random walks on regular languages and algebraic systems of generating functions, and the extendibility of statistical models. There is no index. c. Book News Inc.
| Author | : Alyson Wilson |
| Publisher | : Springer Science & Business Media |
| Total Pages | : 290 |
| Release | : 2007-01-15 |
| Genre | : Mathematics |
| ISBN | : 0387352090 |
Download Statistical Methods in Counterterrorism Book in PDF, ePub and Kindle
With the realization that many clues and hints preceded the September 11 terrorist attacks, statisticians became an important part of the global war on terror. This book surveys emerging research at the intersection of national security and statistical sciences. In it, a diverse group of talented researchers address such topics as Syndromic Surveillance; Modeling and Simulation; Biometric Authentication; and Game Theory. The book includes general reviews of quantitative approaches to counterterrorism, for decision makers with policy backgrounds, as well as technical treatments of statistical issues that will appeal to quantitative researchers.
| Author | : Edoardo M. Airoldi |
| Publisher | : CRC Press |
| Total Pages | : 608 |
| Release | : 2014-11-06 |
| Genre | : Computers |
| ISBN | : 1466504099 |
Download Handbook of Mixed Membership Models and Their Applications Book in PDF, ePub and Kindle
Incorporating more than 20 years of the editors' and contributors' statistical work in mixed membership modeling, this handbook shows how to use these flexible modeling tools to uncover hidden patterns in modern high-dimensional multivariate data. It explores the use of the models in various application settings, including survey data, population genetics, text analysis, image processing and annotation, and molecular biology. Through examples using real data sets, readers will discover how to characterize complex multivariate data in a range of areas.
| Author | : Mayer Alvo |
| Publisher | : Springer Nature |
| Total Pages | : 442 |
| Release | : 2022-11-30 |
| Genre | : Mathematics |
| ISBN | : 3031067843 |
Download Statistical Inference and Machine Learning for Big Data Book in PDF, ePub and Kindle
This book presents a variety of advanced statistical methods at a level suitable for advanced undergraduate and graduate students as well as for others interested in familiarizing themselves with these important subjects. It proceeds to illustrate these methods in the context of real-life applications in a variety of areas such as genetics, medicine, and environmental problems. The book begins in Part I by outlining various data types and by indicating how these are normally represented graphically and subsequently analyzed. In Part II, the basic tools in probability and statistics are introduced with special reference to symbolic data analysis. The most useful and relevant results pertinent to this book are retained. In Part III, the focus is on the tools of machine learning whereas in Part IV the computational aspects of BIG DATA are presented. This book would serve as a handy desk reference for statistical methods at the undergraduate and graduate level as well as be useful in courses which aim to provide an overview of modern statistics and its applications.
