Nonparametric Analysis Of Univariate Heavy Tailed Data

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Nonparametric Analysis of Univariate Heavy-Tailed Data

Author : Natalia Markovich
Publisher : John Wiley & Sons
ISBN 13 : 9780470723593
Total Pages : 336 pages
Book Rating : 4.7/5 (235 download)

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Book Synopsis Nonparametric Analysis of Univariate Heavy-Tailed Data by : Natalia Markovich

Download or read book Nonparametric Analysis of Univariate Heavy-Tailed Data written by Natalia Markovich and published by John Wiley & Sons. This book was released on 2008-03-11 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Heavy-tailed distributions are typical for phenomena in complex multi-component systems such as biometry, economics, ecological systems, sociology, web access statistics, internet traffic, biblio-metrics, finance and business. The analysis of such distributions requires special methods of estimation due to their specific features. These are not only the slow decay to zero of the tail, but also the violation of Cramer’s condition, possible non-existence of some moments, and sparse observations in the tail of the distribution. The book focuses on the methods of statistical analysis of heavy-tailed independent identically distributed random variables by empirical samples of moderate sizes. It provides a detailed survey of classical results and recent developments in the theory of nonparametric estimation of the probability density function, the tail index, the hazard rate and the renewal function. Both asymptotical results, for example convergence rates of the estimates, and results for the samples of moderate sizes supported by Monte-Carlo investigation, are considered. The text is illustrated by the application of the considered methodologies to real data of web traffic measurements.

The Fundamentals of Heavy Tails

Author : Jayakrishnan Nair
Publisher : Cambridge University Press
ISBN 13 : 1009062964
Total Pages : 266 pages
Book Rating : 4.0/5 (9 download)

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Book Synopsis The Fundamentals of Heavy Tails by : Jayakrishnan Nair

Download or read book The Fundamentals of Heavy Tails written by Jayakrishnan Nair and published by Cambridge University Press. This book was released on 2022-06-09 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: Heavy tails –extreme events or values more common than expected –emerge everywhere: the economy, natural events, and social and information networks are just a few examples. Yet after decades of progress, they are still treated as mysterious, surprising, and even controversial, primarily because the necessary mathematical models and statistical methods are not widely known. This book, for the first time, provides a rigorous introduction to heavy-tailed distributions accessible to anyone who knows elementary probability. It tackles and tames the zoo of terminology for models and properties, demystifying topics such as the generalized central limit theorem and regular variation. It tracks the natural emergence of heavy-tailed distributions from a wide variety of general processes, building intuition. And it reveals the controversy surrounding heavy tails to be the result of flawed statistics, then equips readers to identify and estimate with confidence. Over 100 exercises complete this engaging package.

A Practical Guide to Heavy Tails

Author : Robert Adler
Publisher : Springer Science & Business Media
ISBN 13 : 9780817639518
Total Pages : 560 pages
Book Rating : 4.6/5 (395 download)

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Book Synopsis A Practical Guide to Heavy Tails by : Robert Adler

Download or read book A Practical Guide to Heavy Tails written by Robert Adler and published by Springer Science & Business Media. This book was released on 1998-10-26 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Twenty-four contributions, intended for a wide audience from various disciplines, cover a variety of applications of heavy-tailed modeling involving telecommunications, the Web, insurance, and finance. Along with discussion of specific applications are several papers devoted to time series analysis, regression, classical signal/noise detection problems, and the general structure of stable processes, viewed from a modeling standpoint. Emphasis is placed on developments in handling the numerical problems associated with stable distribution (a main technical difficulty until recently). No index. Annotation copyrighted by Book News, Inc., Portland, OR

The Fitness of Information

Author : Chaomei Chen
Publisher : John Wiley & Sons
ISBN 13 : 1118594207
Total Pages : 271 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis The Fitness of Information by : Chaomei Chen

Download or read book The Fitness of Information written by Chaomei Chen and published by John Wiley & Sons. This book was released on 2014-07-30 with total page 271 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theories and practices to assess critical information in a complex adaptive system Organized for readers to follow along easily, The Fitness of Information: Quantitative Assessments of Critical Evidence provides a structured outline of the key challenges in assessing crucial information in a complex adaptive system. Illustrating a variety of computational and explanatory challenges, the book demonstrates principles and practical implications of exploring and assessing the fitness of information in an extensible framework of adaptive landscapes. The book’s first three chapters introduce fundamental principles and practical examples in connection to the nature of aesthetics, mental models, and the subjectivity of evidence. In particular, the underlying question is how these issues can be addressed quantitatively, not only computationally but also explanatorily. The next chapter illustrates how one can reduce the level of complexity in understanding the structure and dynamics of scientific knowledge through the design and use of the CiteSpace system for visualizing and analyzing emerging trends in scientific literature. The following two chapters explain the concepts of structural variation and the fitness of information in a framework that builds on the idea of fitness landscape originally introduced to study population evolution. The final chapter presents a dual-map overlay technique and demonstrates how it supports a variety of analytic tasks for a new type of portfolio analysis. The Fitness of Information: Quantitative Assessments of Critical Evidence also features: In-depth case studies and examples that characterize far-reaching concepts, illustrate underlying principles, and demonstrate profound challenges and complexities at various levels of analytic reasoning Wide-ranging topics that underline the common theme, from the subjectivity of evidence in criminal trials to detecting early signs of critical transitions and mechanisms behind radical patents An extensible and unifying framework for visual analytics by transforming analytic reasoning tasks to the assessment of critical evidence The Fitness of Information: Quantitative Assessments of Critical Evidence is a suitable reference for researchers, analysts, and practitioners who are interested in analyzing evidence and making decisions with incomplete, uncertain, and even conflicting information. The book is also an excellent textbook for upper-undergraduate and graduate-level courses on visual analytics, information visualization, and business analytics and decision support systems.

Matrix Analysis for Statistics

Author : James R. Schott
Publisher : John Wiley & Sons
ISBN 13 : 1119092485
Total Pages : 547 pages
Book Rating : 4.1/5 (19 download)

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Book Synopsis Matrix Analysis for Statistics by : James R. Schott

Download or read book Matrix Analysis for Statistics written by James R. Schott and published by John Wiley & Sons. This book was released on 2016-06-20 with total page 547 pages. Available in PDF, EPUB and Kindle. Book excerpt: An up-to-date version of the complete, self-contained introduction to matrix analysis theory and practice Providing accessible and in-depth coverage of the most common matrix methods now used in statistical applications, Matrix Analysis for Statistics, Third Edition features an easy-to-follow theorem/proof format. Featuring smooth transitions between topical coverage, the author carefully justifies the step-by-step process of the most common matrix methods now used in statistical applications, including eigenvalues and eigenvectors; the Moore-Penrose inverse; matrix differentiation; and the distribution of quadratic forms. An ideal introduction to matrix analysis theory and practice, Matrix Analysis for Statistics, Third Edition features: • New chapter or section coverage on inequalities, oblique projections, and antieigenvalues and antieigenvectors • Additional problems and chapter-end practice exercises at the end of each chapter • Extensive examples that are familiar and easy to understand • Self-contained chapters for flexibility in topic choice • Applications of matrix methods in least squares regression and the analyses of mean vectors and covariance matrices Matrix Analysis for Statistics, Third Edition is an ideal textbook for upper-undergraduate and graduate-level courses on matrix methods, multivariate analysis, and linear models. The book is also an excellent reference for research professionals in applied statistics. James R. Schott, PhD, is Professor in the Department of Statistics at the University of Central Florida. He has published numerous journal articles in the area of multivariate analysis. Dr. Schott’s research interests include multivariate analysis, analysis of covariance and correlation matrices, and dimensionality reduction techniques.

Bayesian Analysis of Stochastic Process Models

Author : David Insua
Publisher : John Wiley & Sons
ISBN 13 : 0470744537
Total Pages : 315 pages
Book Rating : 4.4/5 (77 download)

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Book Synopsis Bayesian Analysis of Stochastic Process Models by : David Insua

Download or read book Bayesian Analysis of Stochastic Process Models written by David Insua and published by John Wiley & Sons. This book was released on 2012-05-07 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian analysis of complex models based on stochastic processes has in recent years become a growing area. This book provides a unified treatment of Bayesian analysis of models based on stochastic processes, covering the main classes of stochastic processing including modeling, computational, inference, forecasting, decision making and important applied models. Key features: Explores Bayesian analysis of models based on stochastic processes, providing a unified treatment. Provides a thorough introduction for research students. Computational tools to deal with complex problems are illustrated along with real life case studies Looks at inference, prediction and decision making. Researchers, graduate and advanced undergraduate students interested in stochastic processes in fields such as statistics, operations research (OR), engineering, finance, economics, computer science and Bayesian analysis will benefit from reading this book. With numerous applications included, practitioners of OR, stochastic modelling and applied statistics will also find this book useful.

Introduction to Time Series Analysis and Forecasting

Author : Douglas C. Montgomery
Publisher : John Wiley & Sons
ISBN 13 : 1118745221
Total Pages : 672 pages
Book Rating : 4.1/5 (187 download)

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Book Synopsis Introduction to Time Series Analysis and Forecasting by : Douglas C. Montgomery

Download or read book Introduction to Time Series Analysis and Forecasting written by Douglas C. Montgomery and published by John Wiley & Sons. This book was released on 2015-03-30 with total page 672 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "…[t]he book is great for readers who need to applythe methods and models presented but have little background inmathematics and statistics." -MAA Reviews Thoroughly updated throughout, Introduction to Time SeriesAnalysis and Forecasting, Second Edition presents theunderlying theories of time series analysis that are needed toanalyze time-oriented data and construct real-world short- tomedium-term statistical forecasts. Authored by highly-experienced academics and professionals inengineering statistics, the Second Edition featuresdiscussions on both popular and modern time series methodologies aswell as an introduction to Bayesian methods in forecasting.Introduction to Time Series Analysis and Forecasting, SecondEdition also includes: Over 300 exercises from diverse disciplines including healthcare, environmental studies, engineering, and finance More than 50 programming algorithms using JMP®, SAS®,and R that illustrate the theory and practicality of forecastingtechniques in the context of time-oriented data New material on frequency domain and spatial temporaldata analysis Expanded coverage of the variogram and spectrum withapplications as well as transfer and intervention modelfunctions A supplementary website featuring PowerPoint®slides, data sets, and select solutions to the problems Introduction to Time Series Analysis and Forecasting, SecondEdition is an ideal textbook upper-undergraduate andgraduate-levels courses in forecasting and time series. The book isalso an excellent reference for practitioners and researchers whoneed to model and analyze time series data to generate forecasts.

Distributed Computer and Communication Networks: Control, Computation, Communications

Author : Vladimir M. Vishnevskiy
Publisher : Springer Nature
ISBN 13 : 3031232070
Total Pages : 447 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Distributed Computer and Communication Networks: Control, Computation, Communications by : Vladimir M. Vishnevskiy

Download or read book Distributed Computer and Communication Networks: Control, Computation, Communications written by Vladimir M. Vishnevskiy and published by Springer Nature. This book was released on 2023-01-01 with total page 447 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed post-conference proceedings of the 25th International Conference on Distributed and Computer and Communication Networks, DCCN 2022, held in Moscow, Russia, in September 26–29, 2022. The 31 revised full papers and 2 revised short papers were carefully reviewed and selected from 130 submissions. The papers cover the following topics: computer and communication networks; analytical modeling of distributed systems; and distributed systems applications.

Nonparametric Statistics

Author : Patrice Bertail
Publisher : Springer
ISBN 13 : 3319969412
Total Pages : 388 pages
Book Rating : 4.3/5 (199 download)

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Book Synopsis Nonparametric Statistics by : Patrice Bertail

Download or read book Nonparametric Statistics written by Patrice Bertail and published by Springer. This book was released on 2019-03-08 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume presents the latest advances and trends in nonparametric statistics, and gathers selected and peer-reviewed contributions from the 3rd Conference of the International Society for Nonparametric Statistics (ISNPS), held in Avignon, France on June 11-16, 2016. It covers a broad range of nonparametric statistical methods, from density estimation, survey sampling, resampling methods, kernel methods and extreme values, to statistical learning and classification, both in the standard i.i.d. case and for dependent data, including big data. The International Society for Nonparametric Statistics is uniquely global, and its international conferences are intended to foster the exchange of ideas and the latest advances among researchers from around the world, in cooperation with established statistical societies such as the Institute of Mathematical Statistics, the Bernoulli Society and the International Statistical Institute. The 3rd ISNPS conference in Avignon attracted more than 400 researchers from around the globe, and contributed to the further development and dissemination of nonparametric statistics knowledge.

Loss Models

Author : Stuart A. Klugman
Publisher : John Wiley & Sons
ISBN 13 : 1118573749
Total Pages : 368 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Loss Models by : Stuart A. Klugman

Download or read book Loss Models written by Stuart A. Klugman and published by John Wiley & Sons. This book was released on 2013-08-29 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: An essential resource for constructing and analyzing advanced actuarial models Loss Models: Further Topics presents extended coverage of modeling through the use of tools related to risk theory, loss distributions, and survival models. The book uses these methods to construct and evaluate actuarial models in the fields of insurance and business. Providing an advanced study of actuarial methods, the book features extended discussions of risk modeling and risk measures, including Tail-Value-at-Risk. Loss Models: Further Topics contains additional material to accompany the Fourth Edition of Loss Models: From Data to Decisions, such as: Extreme value distributions Coxian and related distributions Mixed Erlang distributions Computational and analytical methods for aggregate claim models Counting processes Compound distributions with time-dependent claim amounts Copula models Continuous time ruin models Interpolation and smoothing The book is an essential reference for practicing actuaries and actuarial researchers who want to go beyond the material required for actuarial qualification. Loss Models: Further Topics is also an excellent resource for graduate students in the actuarial field.

Mixed Models

Author : Eugene Demidenko
Publisher : John Wiley & Sons
ISBN 13 : 1118592999
Total Pages : 768 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Mixed Models by : Eugene Demidenko

Download or read book Mixed Models written by Eugene Demidenko and published by John Wiley & Sons. This book was released on 2013-08-26 with total page 768 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition “This book will serve to greatly complement the growing number of texts dealing with mixed models, and I highly recommend including it in one’s personal library.” —Journal of the American Statistical Association Mixed modeling is a crucial area of statistics, enabling the analysis of clustered and longitudinal data. Mixed Models: Theory and Applications with R, Second Edition fills a gap in existing literature between mathematical and applied statistical books by presenting a powerful examination of mixed model theory and application with special attention given to the implementation in R. The new edition provides in-depth mathematical coverage of mixed models’ statistical properties and numerical algorithms, as well as nontraditional applications, such as regrowth curves, shapes, and images. The book features the latest topics in statistics including modeling of complex clustered or longitudinal data, modeling data with multiple sources of variation, modeling biological variety and heterogeneity, Healthy Akaike Information Criterion (HAIC), parameter multidimensionality, and statistics of image processing. Mixed Models: Theory and Applications with R, Second Edition features unique applications of mixed model methodology, as well as: Comprehensive theoretical discussions illustrated by examples and figures Over 300 exercises, end-of-section problems, updated data sets, and R subroutines Problems and extended projects requiring simulations in R intended to reinforce material Summaries of major results and general points of discussion at the end of each chapter Open problems in mixed modeling methodology, which can be used as the basis for research or PhD dissertations Ideal for graduate-level courses in mixed statistical modeling, the book is also an excellent reference for professionals in a range of fields, including cancer research, computer science, and engineering.

Applied Linear Regression

Author : Sanford Weisberg
Publisher : John Wiley & Sons
ISBN 13 : 1118594851
Total Pages : 284 pages
Book Rating : 4.1/5 (185 download)

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Book Synopsis Applied Linear Regression by : Sanford Weisberg

Download or read book Applied Linear Regression written by Sanford Weisberg and published by John Wiley & Sons. This book was released on 2013-11-25 with total page 284 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Third Edition "...this is an excellent book which could easily be used as a course text..." —International Statistical Institute The Fourth Edition of Applied Linear Regression provides a thorough update of the basic theory and methodology of linear regression modeling. Demonstrating the practical applications of linear regression analysis techniques, the Fourth Edition uses interesting, real-world exercises and examples. Stressing central concepts such as model building, understanding parameters, assessing fit and reliability, and drawing conclusions, the new edition illustrates how to develop estimation, confidence, and testing procedures primarily through the use of least squares regression. While maintaining the accessible appeal of each previous edition,Applied Linear Regression, Fourth Edition features: Graphical methods stressed in the initial exploratory phase, analysis phase, and summarization phase of an analysis In-depth coverage of parameter estimates in both simple and complex models, transformations, and regression diagnostics Newly added material on topics including testing, ANOVA, and variance assumptions Updated methodology, such as bootstrapping, cross-validation binomial and Poisson regression, and modern model selection methods Applied Linear Regression, Fourth Edition is an excellent textbook for upper-undergraduate and graduate-level students, as well as an appropriate reference guide for practitioners and applied statisticians in engineering, business administration, economics, and the social sciences.

Understanding Uncertainty

Author : Dennis V. Lindley
Publisher : John Wiley & Sons
ISBN 13 : 1118650239
Total Pages : 434 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis Understanding Uncertainty by : Dennis V. Lindley

Download or read book Understanding Uncertainty written by Dennis V. Lindley and published by John Wiley & Sons. This book was released on 2013-11-26 with total page 434 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the First Edition "...a reference for everyone who is interested in knowing and handling uncertainty." —Journal of Applied Statistics The critically acclaimed First Edition of Understanding Uncertainty provided a study of uncertainty addressed to scholars in all fields, showing that uncertainty could be measured by probability, and that probability obeyed three basic rules that enabled uncertainty to be handled sensibly in everyday life. These ideas were extended to embrace the scientific method and to show how decisions, containing an uncertain element, could be rationally made. Featuring new material, the Revised Edition remains the go-to guide for uncertainty and decision making, providing further applications at an accessible level including: A critical study of transitivity, a basic concept in probability A discussion of how the failure of the financial sector to use the proper approach to uncertainty may have contributed to the recent recession A consideration of betting, showing that a bookmaker's odds are not expressions of probability Applications of the book’s thesis to statistics A demonstration that some techniques currently popular in statistics, like significance tests, may be unsound, even seriously misleading, because they violate the rules of probability Understanding Uncertainty, Revised Edition is ideal for students studying probability or statistics and for anyone interested in one of the most fascinating and vibrant fields of study in contemporary science and mathematics.

Methods and Applications of Linear Models

Author : Ronald R. Hocking
Publisher : John Wiley & Sons
ISBN 13 : 1118329503
Total Pages : 724 pages
Book Rating : 4.1/5 (183 download)

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Book Synopsis Methods and Applications of Linear Models by : Ronald R. Hocking

Download or read book Methods and Applications of Linear Models written by Ronald R. Hocking and published by John Wiley & Sons. This book was released on 2013-08-05 with total page 724 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for the Second Edition "An essential desktop reference book . . . it should definitely be on your bookshelf." —Technometrics A thoroughly updated book, Methods and Applications of Linear Models: Regression and the Analysis of Variance, Third Edition features innovative approaches to understanding and working with models and theory of linear regression. The Third Edition provides readers with the necessary theoretical concepts, which are presented using intuitive ideas rather than complicated proofs, to describe the inference that is appropriate for the methods being discussed. The book presents a unique discussion that combines coverage of mathematical theory of linear models with analysis of variance models, providing readers with a comprehensive understanding of both the theoretical and technical aspects of linear models. With a new focus on fixed effects models, Methods and Applications of Linear Models: Regression and the Analysis of Variance, Third Edition also features: Newly added topics including least squares, the cell means model, and graphical inspection of data in the AVE method Frequent conceptual and numerical examples for clarifying the statistical analyses and demonstrating potential pitfalls Graphics and computations developed using JMP® software to accompany the concepts and techniques presented Numerous exercises presented to test readers and deepen their understanding of the material An ideal book for courses on linear models and linear regression at the undergraduate and graduate levels, the Third Edition of Methods and Applications of Linear Models: Regression and the Analysis of Variance is also a valuable reference for applied statisticians and researchers who utilize linear model methodology.

Structural Equation Modeling

Author : Jichuan Wang
Publisher : John Wiley & Sons
ISBN 13 : 1118356306
Total Pages : 471 pages
Book Rating : 4.1/5 (183 download)

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Book Synopsis Structural Equation Modeling by : Jichuan Wang

Download or read book Structural Equation Modeling written by Jichuan Wang and published by John Wiley & Sons. This book was released on 2012-07-31 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: A reference guide for applications of SEM using Mplus Structural Equation Modeling: Applications Using Mplus is intended as both a teaching resource and a reference guide. Written in non-mathematical terms, this book focuses on the conceptual and practical aspects of Structural Equation Modeling (SEM). Basic concepts and examples of various SEM models are demonstrated along with recently developed advanced methods, such as mixture modeling and model-based power analysis and sample size estimate for SEM. The statistical modeling program, Mplus, is also featured and provides researchers with a flexible tool to analyze their data with an easy-to-use interface and graphical displays of data and analysis results. Key features: Presents a useful reference guide for applications of SEM whilst systematically demonstrating various advanced SEM models, such as multi-group and mixture models using Mplus. Discusses and demonstrates various SEM models using both cross-sectional and longitudinal data with both continuous and categorical outcomes. Provides step-by-step instructions of model specification and estimation, as well as detail interpretation of Mplus results. Explores different methods for sample size estimate and statistical power analysis for SEM. By following the examples provided in this book, readers will be able to build their own SEM models using Mplus. Teachers, graduate students, and researchers in social sciences and health studies will also benefit from this book.

Fast Sequential Monte Carlo Methods for Counting and Optimization

Author : Reuven Y. Rubinstein
Publisher : John Wiley & Sons
ISBN 13 : 1118612353
Total Pages : 177 pages
Book Rating : 4.1/5 (186 download)

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Book Synopsis Fast Sequential Monte Carlo Methods for Counting and Optimization by : Reuven Y. Rubinstein

Download or read book Fast Sequential Monte Carlo Methods for Counting and Optimization written by Reuven Y. Rubinstein and published by John Wiley & Sons. This book was released on 2013-11-13 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive account of the theory and application of Monte Carlo methods Based on years of research in efficient Monte Carlo methods for estimation of rare-event probabilities, counting problems, and combinatorial optimization, Fast Sequential Monte Carlo Methods for Counting and Optimization is a complete illustration of fast sequential Monte Carlo techniques. The book provides an accessible overview of current work in the field of Monte Carlo methods, specifically sequential Monte Carlo techniques, for solving abstract counting and optimization problems. Written by authorities in the field, the book places emphasis on cross-entropy, minimum cross-entropy, splitting, and stochastic enumeration. Focusing on the concepts and application of Monte Carlo techniques, Fast Sequential Monte Carlo Methods for Counting and Optimization includes: Detailed algorithms needed to practice solving real-world problems Numerous examples with Monte Carlo method produced solutions within the 1-2% limit of relative error A new generic sequential importance sampling algorithm alongside extensive numerical results An appendix focused on review material to provide additional background information Fast Sequential Monte Carlo Methods for Counting and Optimization is an excellent resource for engineers, computer scientists, mathematicians, statisticians, and readers interested in efficient simulation techniques. The book is also useful for upper-undergraduate and graduate-level courses on Monte Carlo methods.

Applied Logistic Regression

Author : David W. Hosmer, Jr.
Publisher : John Wiley & Sons
ISBN 13 : 0470582472
Total Pages : 528 pages
Book Rating : 4.4/5 (75 download)

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Book Synopsis Applied Logistic Regression by : David W. Hosmer, Jr.

Download or read book Applied Logistic Regression written by David W. Hosmer, Jr. and published by John Wiley & Sons. This book was released on 2013-04-01 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new edition of the definitive guide to logistic regression modeling for health science and other applications This thoroughly expanded Third Edition provides an easily accessible introduction to the logistic regression (LR) model and highlights the power of this model by examining the relationship between a dichotomous outcome and a set of covariables. Applied Logistic Regression, Third Edition emphasizes applications in the health sciences and handpicks topics that best suit the use of modern statistical software. The book provides readers with state-of-the-art techniques for building, interpreting, and assessing the performance of LR models. New and updated features include: A chapter on the analysis of correlated outcome data A wealth of additional material for topics ranging from Bayesian methods to assessing model fit Rich data sets from real-world studies that demonstrate each method under discussion Detailed examples and interpretation of the presented results as well as exercises throughout Applied Logistic Regression, Third Edition is a must-have guide for professionals and researchers who need to model nominal or ordinal scaled outcome variables in public health, medicine, and the social sciences as well as a wide range of other fields and disciplines.