Parametric and Nonparametric Inference from Record-Breaking Data

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ISBN-13:
9780387001388
Einband:
Paperback
Erscheinungsdatum:
27.01.2003
Seiten:
128
Autor:
Sneh Gulati
Gewicht:
207 g
Format:
235x155x7 mm
Sprache:
Englisch
Beschreibung:

By providing a comprehensive look at statistical inference from record-breaking data in both parametric and nonparametric settings, this book treats the area of nonparametric function estimation from such data in detail. Its main purpose is to fill this void on general inference from record values. Statisticians, mathematicians, and engineers will find the book useful as a research reference. It can also serve as part of a graduate-level statistics or mathematics course.
Analyzing data in the form of records is of particular important to statiticians working with financial and environmental data. This book
summarizes the literature, and presents new results about how future
performance can be predicted from past values.
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.

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