Bøger af N. Balakrishnan

This monograph offers a thorough and updated guide to the theory and methods of progressive censoring, an area that has experienced tremendous growth in recent years. Progressive censoring, originally proposed in the 1950s, is an efficient method of handling samples from industrial experiments involving lifetimes of units that have either failed or censored in a progressive fashion during the life test, with many practical applications to reliability and quality.Key topics and features:Data sets from the literature as well as newly simulated data sets are used to illustrate concepts throughout the textEmphasis on real-life applications to life testing, reliability, and quality controlDiscussion of parametric and nonparametric inferenceCoverage of experimental design with optimal progressive censoringThe Art of Progressive Censoring is a valuable reference for graduate students, researchers, and practitioners inapplied statistics, quality control, life testing, and reliability. With its accessible style and concrete examples, the work may also be used as a textbook in advanced undergraduate or beginning graduate courses on censoring or progressive censoring, as well as a supplementary textbook for a course on ordered data.

Enrique Castillo is a leading figure in several mathematical, statistical, and engineering fields, having contributed seminal work in such areas as statistical modeling, extreme value analysis, multivariate distribution theory, Bayesian networks, neural networks, functional equations, artificial intelligence, linear algebra, optimization methods, numerical methods, reliability engineering, as well as sensitivity analysis and its applications. Organized to honor Castillo's significant contributions, this volume is an outgrowth of the International Conference on Mathematical and Statistical Modeling and covers recent advances in the field. Also presented are applications to safety, reliability and life-testing, financial modeling, quality control, general inference, as well as neural networks and computational techniques.The book is divided into nine major sections:* Distribution Theory and Applications* Probability and Statistics* Order Statistics and Analysis* Engineering Modeling* Extreme Value Theory* Business and Economics Applications* Statistical Methods* Applied Mathematics* Discrete DistributionsThis comprehensive reference work will appeal to a diverse audience from the statistical, applied mathematics, engineering, and economics communities. Practitioners, researchers, and graduate students in mathematical and statistical modeling, optimization, and computing will benefit from this work.

S. Panchapakesan has made significant contributions to ranking and selection and has published in many other areas of statistics, including order statistics, reliability theory, stochastic inequalities, and inference. Written in his honor, the twenty invited articles in this volume reflect recent advances in these fields and form a tribute to Panchapakesan's influence and impact on these areas. Thematically organized, the chapters cover a broad range of topics from:* Inference* Ranking and Selection* Multiple Comparisons and Tests * Agreement Assessment * Reliability * Biostatistics Featuring theory, methods, applications, and extensive bibliographies with special emphasis on recent literature, this comprehensive reference work will serve researchers, practitioners, and graduate students in the statistical and applied mathematics communities.

Parametric and semiparametric models are tools with a wide range of applications to reliability, survival analysis, and quality of life. This self-contained volume examines these tools in survey articles written by experts currently working on the development and evaluation of models and methods. While a number of chapters deal with general theory, several explore more specific connections and recent results in "real-world" reliability theory, survival analysis, and related fields.

This book highlights various theoretical developments on logistic distribution, illustrates the practical utility of these results, and describes univariate and multivariate generalizations of the distribution. It is useful for researchers, practicing statisticians, and graduate students.

This book presents a study of order statistics from standard Inverse Gaussian distributions and their moments, and applies the moments of order statistics to derive the best linear unbiased estimators of the location and scale parameters based on complete as well as Type-II censored samples.

This book offers a thorough and updated guide to the theory and methods of progressive censoring, an area that has experienced tremendous growth over the last decade.

This new book offers a guide to the theory and methods of progressive censoring. In many industrial experiments involving lifetimes of machines or units, experiments have to be terminated early. Progressive Censoring first introduces progressive sampling foundations, and then discusses various properties of progressive samples.

Inverse Gaussian distribution has become one of the most important and widely employed distributions, and is often used to model the lifetimes of components. This handbook covers Inverse Gaussian distribution. It is suitable for members of the statistical community and also to applied scientists, engineers, and econometricians.

This book highlights various theoretical developments on logistic distribution, illustrates the practical utility of these results, and describes univariate and multivariate generalizations of the distribution. It is useful for researchers, practicing statisticians, and graduate students.

This book explains how mathematics can be utilized to provide efficient techniques for implementing effective coverage, deployment, transmission, data processing, signal processing, and data protection within distributed sensor networks.

This new book offers a guide to the theory and methods of progressive censoring. In many industrial experiments involving lifetimes of machines or units, experiments have to be terminated early. Progressive Censoring first introduces progressive sampling foundations, and then discusses various properties of progressive samples.

The conference was organized jointly by St. Petersburg State University, St. Petersburg branch of Mathematical Institute, and the Euler Institute, and was partially sponsored by the Russian Foundation of Basic Researches.

Intended as a reference book and guide for those who study the gas/particle ratios of semi volatile atmospheric compounds, this text carries the world's leading researchers explanations for the theory and practice of gas/particle phase measurements.

Introduces the general theory of order statistics and their applications. The book covers topics such as distribution theory for order statistics from continuous and discrete populations, moment relations, bounds and approximations, order statistics in statistical inference and characterization results, and basic asymptotic theory

Along with a review of general developments relating to bivariate distributions, this volume also covers copulas, a subject which has grown immensely in recent years. In addition, it examines conditionally specified distributions and skewed distributions.

Presents an evaluation of life-testing and reliability. This book includes topics such as interference under censoring and truncation, reliability growth models, designs to improve quality, prediction techniques, Bayesian analysis of reliability, multivariate methods and accelerated testing.

Contains articles that review developments in theoretical and applied statistical science. This work highlights noteworthy results, illustrates their applications, and points out possible directions for future research. It also includes an account of statistical discoveries, references, and many figures and tables.

Covers important topics in the area of Survival Analysis. This book features chapters which provide a comprehensive review of the topic. It also contains examples to demonstrate the methodologies developed and includes a list of important references in the area of Survival Analysis.

Lognormal distributions are one of the most commonly studied models in the sta tistical literature while being most frequently used in the applied literature.