Wiley Series in Probability and Statistics
2 primary works • 3 total works
Book 904
Sequential Estimation
by Malay Ghosh, Nitis Mukhopadhyay, and Pranab Kumar Sen
Published 27 March 1997
This book devoted to sequential estimation presents the advances of the past fifteen years including those in the areas of three--stage accelerated sequential sampling procedures. It integrates the diversities in sequential estimation in a logical, treating both classical and modern techniques and including parametric and nonparametric methods.
Book 912
Constrained Statistical Inference
by Mervyn J. Silvapulle and Pranab Kumar Sen
Published 19 November 2004
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
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
A broad and unified methodology for robust statistics--with exciting new applicationsRobust statistics is one of the fastest growing fields in contemporary statistics. It is also one of the more diverse and sometimes confounding areas, given the many different assessments and interpretations of robustness by theoretical and applied statisticians. This innovative book unifies the many varied, yet related, concepts of robust statistics under a sound theoretical modulation. It seamlessly integrates asymptotics and interrelations, and provides statisticians with an effective system for dealing with the interrelations between the various classes of procedures.Drawing on the expertise of researchers from around the world, and covering over a decade's worth of developments in the field, Robust Statistical Procedures: Asymptotics and Interrelations: * Discusses both theory and applications in its two parts, from the fundamentals to robust statistical inference * Thoroughly explores the interrelations between diverse classes of procedures, unlike any other book * Compares nonparametric procedures with robust statistics, explaining in detail asymptotic representations for various estimators * Provides a timesaving list of mathematical tools for the problems under discussion * Keeps mathematical abstractions to a minimum, in spite of its largely theoretical content * Includes useful problems and exercises at the end of each chapter * Offers strategies for more complex models when using robust statistical procedures Self-contained and rounded in approach, this book is invaluable for both applied statisticians and theoretical researchers; for graduate students in mathematical statistics; and for anyone interested in the influence of this methodology.