Wiley Series in Probability and Statistics
9 primary works • 22 total works
Book 1
Continuous Multivariate Distributions
by N. Balakrishnan, Samuel Kotz, and Norman L. Johnson
Book 3
Book 327
Sensitivity Analysis in Linear Regression
by Samprit Chatterjee and Ali S. Hadi
Book 334
Continuous Multivariate Distributions, Volume 1
by Samuel Kotz, N. Balakrishnan, and Norman L. Johnson
Book 444
Univariate Discrete Distrbutions 3e
by Norman L. Johnson, Adrienne W. Kemp, and Samuel Kotz
Beginning with mathematical, probability, and statistical fundamentals, the authors provide clear coverage of the key topics in the field, and includes: Families of discrete distributions; Binomial distribution; Poisson distribution; Negative binomial distribution; Hypergeometric distributions; Logarithmic and Lagrangian distributions; Mixture distributions; Stopped-sum distributions; Matching, occupancy, runs, and q-series distributions; and Parametric regression models and miscellaneas. Emphasis continues to be placed on the increasing relevance of Bayesian inference to discrete distribution, especially with regard to the binomial and Poisson distributions. New derivations of discrete distributions via stochastic processes and random walks are introduced without unnecessarily complex discussions of stochastic processes. Throughout the third edition, extensive information has been added to reflect the new role of computer-based applications. With its thorough coverage and balanced presentation of theory and application, this is an excellent and essential reference for statisticians and mathematicians.
Book 472
The book features the following parts: Part A deals with the original precedence test and some properties of precedence and related test procedures Part B explores alternatives to precedence testing, including maximal precedence, weighted forms of precedence and maximal precedence, and Wilcoxon-type rank-sum precedence tests and their properties Part C compares the extension of precedence, maximal precedence, and Wilcoxon-type rank-sum precedence tests to situations in which the sample arising from the life-testing experiment is progressively Type-II censored Part D examines precedence-type tests in multi-sample situations and selection problems Tables are presented throughout the book to facilitate the application of the tests to practical problems. Helpful examples illustrate all of the precedence-type procedures, and an extensive bibliography enables readers to explore specialized topics in greater depth. This book is a recommended reference for researchers and practitioners in reliability and life-time data analysis, applied probabilists, and engineers. It also serves as a supplemental text for courses in nonparametric statistics and reliability.
Book 728
Statistical Size Distributions in Economics and Actuarial Sciences
by Christian Kleiber and Samuel Kotz
Specific models covered include:* Pareto distributions* Lognormal distributions* Gamma-type size distributions* Beta-type size distributions* Miscellaneous size distributions Three appendices provide brief biographies of some of the leading players along with the basic properties of each of the distributions. Actuaries, economists, market researchers, social scientists, and physicists interested in econophysics will find Statistical Size Distributions in Economics and Actuarial Sciences to be a truly one-of-a-kind addition to the professional literature.
Book 764
Book 768
The book follows a rational textbook format, featuring witty and insightful chapter introductions that help smooth transitions from one topic to another and challenging chapter-end exercises, which expand on the material covered. An extensive bibliography and numerous references throughout the text specify sources for further readings on relevant topics. Records is a valuable professional resource for probabilists and statisticians, in addition to applied statisticians, meteorologists, hydrologists, market analysts, and sports analysts. It also makes an excellent primary text for courses in record theory and a supplement to order statistics courses.
Discrete Multivariate Distributions
by Norman L. Johnson, Samuel Kotz, and N. Balakrishnan
Originally planned as a revision of Chapter 11 of that classic, this project soon blossomed into a substantial volume as a result of the unprecedented growth that has occurred in the literature on discrete multivariate distributions and their applications over the past quarter century. The only comprehensive, single-volume work on the subject, this valuable reference affords statisticians direct access to all of the latest developments concerning discrete multivariate distributions. Concentrating primarily on areas of interest to theoretical as well as applied statisticians, the authors provide complete coverage of several important discrete multivariate distributions. These include multinomial, binomial, negative binomial, Poisson, power series, hypergeometric, Polya-Eggenberger, Ewens, orders, and some families of distributions. Discrete Multivariate Distributions begins with a general overview of the multivariate method in which the authors lay the basic theoretical groundwork for the discussions that follow.
For clarity and consistency, subsequent chapters follow a similar format, beginning with a concise historical account followed by a discussion of properties and characteristics. Coverage then advances to in-depth explorations of inferential issues and applications, liberally supplemented with helpful details and a collection of real-world applications obtained from the authors' extensive searches of current literature worldwide. Discrete Multivariate Distributions is an essential working resource for researchers, professionals, practitioners, and graduate students in statistics, mathematics, computer science, engineering, medicine, and the biological sciences.
Continuous Univariate Distributions 2e V 1
by Norman L. Johnson, Samuel Kotz, and N. Balakrishnan
Continuous Univariate Distributions 2e V 2
by Norman L. Johnson, Samuel Kotz, and N. Balakrishnan
Extreme Value and Related Models with Applications in Engineering and Science
by Enrique Castillo, Ali S. Hadi, N. Balakrishnan, and Jose M. Sarabia
The book provides:* A unique focus on modern topics including data analysis and inference* Specific data in such areas as wind, flood, chain strength, electrical insulation, fatigue, precipitation, and wave heights* Useful techniques for addressing extreme value problems, including discrete, continuous, univariate, and multivariate models* Coverage of order statistics, return period, exceedances and shortfalls, along with detailed explanations on how to obtain exact distributions for these statistics* An in--depth look at asymptotic models and the limit distributions of maxima, minima, and other order statistics Enhanced with numerous graphs and exercises, plus an extensive bibliography for further study, this text is an important reference source for engineers designing structures that will withstand even the most extreme circumstances.
Handbook of Regression Analysis With Applications in R
by Samprit Chatterjee and Jeffrey S. Simonoff
Handbook and reference guide for students and practitioners of statistical regression-based analyses in R
Handbook of Regression Analysis with Applications in R, Second Edition is a comprehensive and up-to-date guide to conducting complex regressions in the R statistical programming language. The authors’ thorough treatment of “classical” regression analysis in the first edition is complemented here by their discussion of more advanced topics including time-to-event survival data and longitudinal and clustered data.
The book further pays particular attention to methods that have become prominent in the last few decades as increasingly large data sets have made new techniques and applications possible. These include:
- Regularization methods
- Smoothing methods
- Tree-based methods
In the new edition of the Handbook, the data analyst’s toolkit is explored and expanded. Examples are drawn from a wide variety of real-life applications and data sets. All the utilized R code and data are available via an author-maintained website.
Of interest to undergraduate and graduate students taking courses in statistics and regression, the Handbook of Regression Analysis will also be invaluable to practicing data scientists and statisticians.
Introduction to Probability – Models and Applications
by N. Balakrishnan, Markos V. Koutras, and Konstadinos G. Politis
Advanced Regression Model Building Techniques
by Samprit Chatterjee and Surajit Ray
Presents statistical methodologies for analyzing common types of data from method comparison experiments and illustrates their applications through detailed case studies
Measuring Agreement: Models, Methods, and Applications features statistical evaluation of agreement between two or more methods of measurement of a variable with a primary focus on continuous data. The authors view the analysis of method comparison data as a two-step procedure where an adequate model for the data is found, and then inferential techniques are applied for appropriate functions of parameters of the model. The presentation is accessible to a wide audience and provides the necessary technical details and references. In addition, the authors present chapter-length explorations of data from paired measurements designs, repeated measurements designs, and multiple methods; data with covariates; and heteroscedastic, longitudinal, and categorical data. The book also:
- Strikes a balance between theory and applications
- Presents parametric as well as nonparametric methodologies
- Provides a concise introduction to Cohen's kappa coefficient and other measures of agreement for binary and categorical data
- Discusses sample size determination for trials on measuring agreement
- Contains real-world case studies and exercises throughout
- Provides a supplemental website containing the related datasets and R code
Measuring Agreement: Models, Methods, and Applications is a resource for statisticians and biostatisticians engaged in data analysis, consultancy, and methodological research. It is a reference for clinical chemists, ecologists, and biomedical and other scientists who deal with development and validation of measurement methods. This book can also serve as a graduate-level text for students in statistics and biostatistics.