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Table of contents (7 chapters)
Keywords
About this book
Reviews
New record values in sports, finances, climate, ... are of interest to most people, and for about half a century, probabilists and statisticians have taken up the challenge of modelling their behaviour. The present monograph provides results on statistical inference problems for record-breaking data. For example: how to fit a parametric or nonparametric model to such data? Or also: how to predict the next record, based on the values of the past records. The main body of the book (Chapters 4-7) is a discussion of all the known work on nonparametric inference for this type of data.
The book will be a useful reference for researchers in this area. There could also be interest from engineers working in destructive stress testing and quality control.
ISI Short Book Reviews, Vol. 23/2, August 2003
Authors and Affiliations
Bibliographic Information
Book Title: Parametric and Nonparametric Inference from Record-Breaking Data
Authors: Sneh Gulati, William J. Padgett
Series Title: Lecture Notes in Statistics
DOI: https://doi.org/10.1007/978-0-387-21549-5
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media New York 2003
Softcover ISBN: 978-0-387-00138-8Published: 27 January 2003
eBook ISBN: 978-0-387-21549-5Published: 14 March 2013
Series ISSN: 0930-0325
Series E-ISSN: 2197-7186
Edition Number: 1
Number of Pages: VIII, 117
Number of Illustrations: 2 b/w illustrations
Topics: Statistical Theory and Methods