Sequential Estimation

The only comprehensive guide to the theory and practice of one of today′s most important probabilistic techniques
The past 15 years have witnessed many significant advances in sequential estimation, especially in the areas of three–stage and nonparametric methodology. Yet, until now, there were no references devoted exclusively to this rapidly growing statistical field.
Sequential Estimation is the first, single–source guide to the theory and practice of both classical and modern sequential estimation techniques—including parametric and nonparametric methods. Researchers in sequential analysis will appreciate the unified, logically integrated treatment of the subject, as well as coverage of important contemporary procedures not covered in more general sequential analysis texts, such as: Shrinkage estimation Empirical and hierarchical Bayes procedures Multistage sampling and accelerated sampling procedures Time–sequential estimation Sequential estimation in finite population sampling Reliability estimation and capture–recapture methodologies leading to sequential tagging schemes
An indispensable resource for researchers in sequential analysis, Sequential Estimation is an ideal graduate–level text as well.

Spis treści:
Introduction and Coverage.
Probabilistic Results in Sequential Analysis.
Some Basic Concepts for Fixed–Sample Estimation.
General Aspects of Sequential Estimation.
Sequential Bayesian Estimation.
Multistage Estimation.
Parametric Sequential Point Estimation.
Parametric Sequential Confidence Estimation.
Nonparametric Sequential Point Estimation.
Nonparametric Sequential Confidence Estimation.
Estimation Following Sequential Tests.
Time–Sequential Estimation Problems.
Sequential Estimation in Reliability Models.
Sequential Estimation of the Size of a Finite Population.
Stochastic Approximation .
References.
Indexes.

Nota biograficzna:
MALAY GHOSH, PhD, is a professor in the University of Florida Department of Statistics.
NITIS MUKHOPADHYAY, PhD, is a professor in the University of Connecticut Department of Statistics.
PRANAB K. SEN, PhD, is a professor in the Department of Biostatistics and Statistics of the University of North Carolina.

Okładka tylna:
The only comprehensive guide to the theory and practice of one of today′s most important probabilistic techniques
The past 15 years have witnessed many significant advances in sequential estimation, especially in the areas of three–stage and nonparametric methodology. Yet, until now, there were no references devoted exclusively to this rapidly growing statistical field.
Sequential Estimation is the first, single–source guide to the theory and practice of both classical and modern sequential estimation techniques—including parametric and nonparametric methods. Researchers in sequential analysis will appreciate the unified, logically integrated treatment of the subject, as well as coverage of important contemporary procedures not covered in more general sequential analysis texts, such as: Shrinkage estimation Empirical and hierarchical Bayes procedures Multistage sampling and accelerated sampling procedures Time–sequential estimation Sequential estimation in finite population sampling Reliability estimation and capture–recapture methodologies leading to sequential tagging schemes
An indispensable resource for researchers in sequential analysis, Sequential Estimation is an ideal graduate–level text as well.