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.
Probabilistic Results in Sequential Analysis.
Some Basic Concepts for Fixed–Sample Estimation.
General Aspects of Sequential Estimation.
Sequential Bayesian 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.
"...sequential estimation...is the focus...including both parametric and nonparametric methods..." (Quarterly of Applied Mathematics, Vol. LIX, No. 3, September 2001)
"an excellent source for all researchers in the field" (Statistics & Decisions, Vol.20, No.1, 2002)