Parametric and Nonparametric Inference from Record-Breaking Data
by Gulati, Sneh
This book provides a comprehensive look at statistical inference from record-breaking data in both parametric and nonparametric settings, including Bayesian inference. A unique feature is that it treats the area of nonparametric function estimation from such data in detail, gathering results on this topic to date in one accessible volume. Previous books on records have focused mainly on the probabilistic behavior of records, prediction of future records, and characterizations of the distributio…
Read More ↓Title Statements
- Full title :Parametric and Nonparametric Inference from Record-Breaking Data / by Sneh Gulati, William J. Padgett.
Summary
This book provides a comprehensive look at statistical inference from record-breaking data in both parametric and nonparametric settings, including Bayesian inference. A unique feature is that it treats the area of nonparametric function estimation from such data in detail, gathering results on this topic to date in one accessible volume. Previous books on records have focused mainly on the probabilistic behavior of records, prediction of future records, and characterizations of the distributions of record values, addressing some inference methods only briefly. The main purpose of this book is to fill this void on general inference from record values. Statisticians, mathematicians, and engineers will find the book useful as a research reference and in learning about making inferences from record-breaking data. The book can also serve as part of a graduate- level statistics or mathematics course, complementing material on the probabilistic aspects of record values. For a basic understanding of the statistical concepts, a one-year graduate course in mathematical statistics provides sufficient background. For a detailed understanding of the convergence theory of the nonparametric function estimators, a course in measure theory or probability theory at the graduate level is useful. Sneh Gulati is Associate Professor of Statistics at Florida International University in Miami. She is currently an associate editor of the Journal of Statistical Computation and Simulation and has published several articles in statistics. Currently she serves as the president of the South Florida Chapter of the American Statistical Association and is also the chair of the Florida Commission of Hurricane Loss Projection Methodology. William J. Padgett is Professor of Statistics and was the founding Chair of the Department of Statistics at the University of South.
Read More ↓Edition Statements
- Publication Date:2003.
Publication Statements
- Publisher(s):Springer New York
- Place of Publication:New York, NY
- Language:eng
- Publication Date:2003.
The Physical Object
- Description:1 online resource (viii, 117 pages)
Edition Identifiers
- ISBN:9780387215495, 0387215492
- DOI:10.1007/978-0-387-21549-5
- oclc:ocn853266642
- LC Classification:QA276-280
- Dewey Decimal:519.5
Table of Contents
1. Introduction -- 2. Preliminaries and Early Work -- 3. Parametric Inference -- 4. Nonparametric Inference -- Genesis -- 5. Smooth Function Estimation -- 6. Bayesian Models -- 7. Record Models with Trend -- References.
Read More ↓Subjects
Writers
More from this Series
No reviews yet. Be the first to rate this work.
Related Works
more →
Geometry driven statistics
Statistical data analysis
Algebraic methods in statistics and probability
Mathematical statistics and stochastic processes
Complex stochastic systems
Files & Downloads
-
Parametric and nonparametric inference from recor…
DJVU · 827.0 KB · updated -
Parametric and Nonparametric Inference from Recor…
PDF · 3.0 MB · updated
Rate & Review