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Book Probability Models and Statistical Analyses for Ranking Data

Download or read book Probability Models and Statistical Analyses for Ranking Data written by Michael A. Fligner and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Probability Models and Statistical Analyses for Ranking Data

Download or read book Probability Models and Statistical Analyses for Ranking Data written by Michael A Fligner and published by . This book was released on 1992-11-05 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Book Analyzing and Modeling Rank Data

Download or read book Analyzing and Modeling Rank Data written by John I Marden and published by CRC Press. This book was released on 2014-01-23 with total page 345 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Book Statistical Methods for Ranking Data

Download or read book Statistical Methods for Ranking Data written by Mayer Alvo and published by Springer. This book was released on 2014-09-02 with total page 276 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Probability Models and Statistical Analyses for Ranking Data

Download or read book Probability Models and Statistical Analyses for Ranking Data written by Michael A. Fligner and published by Springer. This book was released on 1992-11-05 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book of edited contributions provides a wide-ranging survey of the use of probability models for ranking data and it introduces new methods for the statistical analysis of ranking data. The contributors are drawn from a variety of fields including psychology, sociology, and the health sciences as well as statistics. Consequently, many researchers whose work involves the study of ranked data will find much of practical interest here. The papers cover the following topics: basic models and mixture models; inference from full and partial rankings; amalgamation and consensus; and paired ranking and unfolding. A foreward by Persi Diaconis draws together some of the mathematical ideas underlying this subject and explores its links with the statistical analysis of permutations.

Book Models for Probability and Statistical Inference

Download or read book Models for Probability and Statistical Inference written by James H. Stapleton and published by John Wiley & Sons. This book was released on 2007-12-14 with total page 466 pages. Available in PDF, EPUB and Kindle. Book excerpt: This concise, yet thorough, book is enhanced with simulations and graphs to build the intuition of readers Models for Probability and Statistical Inference was written over a five-year period and serves as a comprehensive treatment of the fundamentals of probability and statistical inference. With detailed theoretical coverage found throughout the book, readers acquire the fundamentals needed to advance to more specialized topics, such as sampling, linear models, design of experiments, statistical computing, survival analysis, and bootstrapping. Ideal as a textbook for a two-semester sequence on probability and statistical inference, early chapters provide coverage on probability and include discussions of: discrete models and random variables; discrete distributions including binomial, hypergeometric, geometric, and Poisson; continuous, normal, gamma, and conditional distributions; and limit theory. Since limit theory is usually the most difficult topic for readers to master, the author thoroughly discusses modes of convergence of sequences of random variables, with special attention to convergence in distribution. The second half of the book addresses statistical inference, beginning with a discussion on point estimation and followed by coverage of consistency and confidence intervals. Further areas of exploration include: distributions defined in terms of the multivariate normal, chi-square, t, and F (central and non-central); the one- and two-sample Wilcoxon test, together with methods of estimation based on both; linear models with a linear space-projection approach; and logistic regression. Each section contains a set of problems ranging in difficulty from simple to more complex, and selected answers as well as proofs to almost all statements are provided. An abundant amount of figures in addition to helpful simulations and graphs produced by the statistical package S-Plus(r) are included to help build the intuition of readers.

Book Stochastic Epidemic Models and Their Statistical Analysis

Download or read book Stochastic Epidemic Models and Their Statistical Analysis written by Hakan Andersson and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 140 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book The Statistical Analysis of Experimental Data

Download or read book The Statistical Analysis of Experimental Data written by John Mandel and published by Courier Corporation. This book was released on 2012-06-08 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: First half of book presents fundamental mathematical definitions, concepts, and facts while remaining half deals with statistics primarily as an interpretive tool. Well-written text, numerous worked examples with step-by-step presentation. Includes 116 tables.

Book Metric Methods for Analyzing Partially Ranked Data

Download or read book Metric Methods for Analyzing Partially Ranked Data written by Douglas E. Critchlow and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 225 pages. Available in PDF, EPUB and Kindle. Book excerpt: A full ranking of n items is simply an ordering of all these items, of the form: first choice, second choice, •. . , n-th choice. If two judges each rank the same n items, statisticians have used various metrics to measure the closeness of the two rankings, including Ken dall's tau, Spearman's rho, Spearman's footrule, Ulam's metric, Hal1l11ing distance, and Cayley distance. These metrics have been em ployed in many contexts, in many applied statistical and scientific problems. Thi s monograph presents genera 1 methods for extendi ng these metri cs to partially ranked data. Here "partially ranked data" refers, for instance, to the situation in which there are n distinct items, but each judge specifies only his first through k-th choices, where k

Book The Statistical Analysis of Failure Time Data

Download or read book The Statistical Analysis of Failure Time Data written by John D. Kalbfleisch and published by John Wiley & Sons. This book was released on 2011-01-25 with total page 462 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Statistical Methods in Counterterrorism

Download or read book Statistical Methods in Counterterrorism written by Alyson Wilson and published by Springer Science & Business Media. This book was released on 2007-01-15 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Algebraic Methods in Statistics and Probability

Download or read book Algebraic Methods in Statistics and Probability written by Marlos A. G. Viana and published by American Mathematical Soc.. This book was released on 2001 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Introduction to Reliability Analysis

Download or read book Introduction to Reliability Analysis written by Shelemyahu Zacks and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reliability analysis is concerned with the analysis of devices and systems whose individual components are prone to failure. This textbook presents an introduction to reliability analysis of repairable and non-repairable systems. It is based on courses given to both undergraduate and graduate students of engineering and statistics as well as in workshops for professional engineers and scientists. As aresult, the book concentrates on the methodology of the subject and on understanding theoretical results rather than on its theoretical development. An intrinsic aspect of reliability analysis is that the failure of components is best modelled using techniques drawn from probability and statistics. Professor Zacks covers all the basic concepts required from these subjects and covers the main modern reliability analysis techniques thoroughly. These include: the graphical analysis of life data, maximum likelihood estimation and bayesian likelihood estimation. Throughout the emphasis is on the practicalities of the subject with numerous examples drawn from industrial and engineering settings.

Book Handbook of Mixed Membership Models and Their Applications

Download or read book Handbook of Mixed Membership Models and Their Applications written by Edoardo M. Airoldi and published by CRC Press. This book was released on 2014-11-06 with total page 608 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Statistical Inference and Machine Learning for Big Data

Download or read book Statistical Inference and Machine Learning for Big Data written by Mayer Alvo and published by Springer Nature. This book was released on 2022-11-30 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Book Choice Modelling

    Book Details:
  • Author : Stephane Hess
  • Publisher : Emerald Group Publishing
  • Release : 2010-01-15
  • ISBN : 1849507724
  • Pages : 639 pages

Download or read book Choice Modelling written by Stephane Hess and published by Emerald Group Publishing. This book was released on 2010-01-15 with total page 639 pages. Available in PDF, EPUB and Kindle. Book excerpt: Contains a selection of the best theoretical and applied papers from the inaugural International Choice Modelling Conference. The conference was organised by the Institute for Transport Studies at the University of Leeds and held in Harrogate, North Yorkshire on 30 March to 1 April 2009.

Book Applied Latent Class Analysis

Download or read book Applied Latent Class Analysis written by Jacques A. Hagenaars and published by Cambridge University Press. This book was released on 2002-06-24 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Latent Class Analysis introduces several innovations in latent class analysis to a wider audience of researchers. Many of the world's leading innovators in the field of latent class analysis contributed essays to this volume, each presenting a key innovation to the basic latent class model and illustrating how it can prove useful in situations typically encountered in actual research.