Pitman's Measure of Closeness
Pitman's Measure of Closeness

Author: Jerome P. Keating

Publisher: SIAM

Published: 1993-01-01

Total Pages: 236

ISBN-13: 0898713080

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This book provides a thorough introduction to the methods and known results associated with PMC.

Distributions With Given Marginals and Statistical Modelling
Distributions With Given Marginals and Statistical Modelling

Author: Carles M. Cuadras

Publisher: Springer Science & Business Media

Published: 2013-11-11

Total Pages: 252

ISBN-13: 9401700613

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This volume contains the papers presented at the meeting "Distributions with given marginals and statistical modelling", held in Barcelona (Spain), July 17- 20, 2000. This is the fourth meeting on given marginals, showing that this topic has aremarkable interest. BRIEF HISTORY The construction of distributions with given marginals started with the seminal papers by Hoeffding (1940) and Fn!chet (1951). Since then, many others have contributed on this topic: Dall' Aglio, Farlie, Gumbel, Johnson, Kellerer, Kotz, Morgenstern, Marshali, Olkin, Strassen, Vitale, Whitt, etc., as weIl as Arnold, Cambanis, Deheuvels, Genest, Frank, Joe, Kirneldorf, Nelsen, Rüschendorf, Sampson, Scarsini, Tiit, etc. In 1957 Sklar and Schweizer introduced probabilistic metric spaces. In 1975 Kirneldorf and Sampson studied the uniform representation of a bivariate dis tribution and proposed the desirable conditions that should be satisfied by any bivariate family. In 1991 Darsow, Nguyen and Olsen defined a natural operation between cop ulas, with applications in stochastic processes. In 1993, AIsina, Nelsen and Schweizer introduced the notion of quasi-copula

Ordered Data Analysis, Modeling and Health Research Methods
Ordered Data Analysis, Modeling and Health Research Methods

Author: Pankaj Choudhary

Publisher: Springer

Published: 2015-12-14

Total Pages: 268

ISBN-13: 3319254332

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This volume presents an eclectic mix of original research articles in areas covering the analysis of ordered data, stochastic modeling and biostatistics. These areas were featured in a conference held at the University of Texas at Dallas from March 7 to 9, 2014 in honor of Professor H. N. Nagaraja’s 60th birthday and his distinguished contributions to statistics. The articles were written by leading experts who were invited to contribute to the volume from among the conference participants. The volume is intended for all researchers with an interest in order statistics, distribution theory, analysis of censored data, stochastic modeling, time series analysis, and statistical methods for the health sciences, including statistical genetics.

Constrained Statistical Inference
Constrained Statistical Inference

Author: Mervyn J. Silvapulle

Publisher: John Wiley & Sons

Published: 2011-09-15

Total Pages: 560

ISBN-13: 1118165632

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An up-to-date approach to understanding statistical inference Statistical inference is finding useful applications in numerous fields, from sociology and econometrics to biostatistics. This volume enables professionals in these and related fields to master the concepts of statistical inference under inequality constraints and to apply the theory to problems in a variety of areas. Constrained Statistical Inference: Order, Inequality, and Shape Constraints provides a unified and up-to-date treatment of the methodology. It clearly illustrates concepts with practical examples from a variety of fields, focusing on sociology, econometrics, and biostatistics. The authors also discuss a broad range of other inequality-constrained inference problems that do not fit well in the contemplated unified framework, providing a meaningful way for readers to comprehend methodological resolutions. Chapter coverage includes: Population means and isotonic regression Inequality-constrained tests on normal means Tests in general parametric models Likelihood and alternatives Analysis of categorical data Inference on monotone density function, unimodal density function, shape constraints, and DMRL functions Bayesian perspectives, including Stein’s Paradox, shrinkage estimation, and decision theory

Improving Efficiency by Shrinkage
Improving Efficiency by Shrinkage

Author: Marvin Gruber

Publisher: Routledge

Published: 2017-11-01

Total Pages: 648

ISBN-13: 1351439162

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Offers a treatment of different kinds of James-Stein and ridge regression estimators from a frequentist and Bayesian point of view. The book explains and compares estimators analytically as well as numerically and includes Mathematica and Maple programs used in numerical comparison.;College or university bookshops may order five or more copies at a special student rate, available on request.

Empirical Bayes and Likelihood Inference
Empirical Bayes and Likelihood Inference

Author: S.E. Ahmed

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 242

ISBN-13: 1461301416

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Bayesian and such approaches to inference have a number of points of close contact, especially from an asymptotic point of view. Both emphasize the construction of interval estimates of unknown parameters. In this volume, researchers present recent work on several aspects of Bayesian, likelihood and empirical Bayes methods, presented at a workshop held in Montreal, Canada. The goal of the workshop was to explore the linkages among the methods, and to suggest new directions for research in the theory of inference.

Hybrid Censoring Know-How
Hybrid Censoring Know-How

Author: Narayanaswamy Balakrishnan

Publisher: Academic Press

Published: 2023-01-06

Total Pages: 408

ISBN-13: 0123983908

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Hybrid Censoring Know-How: Models, Methods and Applications focuses on hybrid censoring, an important topic in censoring methodology with numerous applications. The readers will find information on the significance of censored data in theoretical and applied contexts, and descriptions of extensive data sets from life-testing experiments where these forms of data naturally occur. The existing literature on censoring methodology, life-testing procedures, and lifetime data analysis provides only hybrid censoring schemes, with little information about hybrid censoring methodologies, ideas, and statistical inferential methods. This book fills that gap, featuring statistical tools applicable to data from medicine, biology, public health, epidemiology, engineering, economics, and demography. - Presents many numerical examples to adequately illustrate all inferential methods discussed - Mentions some open problems and possible directions for future work - Reviews developments on Type-II and Type-I HCS, including the most recent research and trends - Explains why hybrid censored sampling is important in practice - Provides details about the use of HCS under different settings and on various designs of HCS - Describes the use of hybrid censoring in other reliability applications such as reliability sampling plans, step-stress testing, and quality control