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Can I read Parametric and Nonparametric Inference from Record-Breaking Data (Lecture Notes in Statistics, 172) on EtoBox?
Parametric and Nonparametric Inference from Record-Breaking Data (Lecture Notes in Statistics, 172) by Gulati, Sneh, Padgett, William J. is a mathematics available to read on EtoBox.
What is Parametric and Nonparametric Inference from Record-Breaking Data (Lecture Notes in Statistics, 172) about?
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 distribution
Who reads Parametric and Nonparametric Inference from Record-Breaking Data (Lecture Notes in Statistics, 172)?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Gulati, Sneh, Padgett, William J.
- Publisher
- Springer New York : Imprint : Springer
- Published
- 2003
- Language
- EN
- ISBN
- 9780387215495
- Category
- mathematics
- Subjects
- Mathematics, Medical, Reference
- Updated
- 2026-03-25
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