Nonparametric Goodness-of-Fit Testing Under Gaussian Models

Nonparametric Goodness-of-Fit Testing Under Gaussian Models
Author :
Publisher : Springer Science & Business Media
Total Pages : 471
Release :
ISBN-10 : 9780387215808
ISBN-13 : 0387215808
Rating : 4/5 (08 Downloads)

Book Synopsis Nonparametric Goodness-of-Fit Testing Under Gaussian Models by : Yuri Ingster

Download or read book Nonparametric Goodness-of-Fit Testing Under Gaussian Models written by Yuri Ingster and published by Springer Science & Business Media. This book was released on 2012-11-12 with total page 471 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the modern theory of nonparametric goodness-of-fit testing. It fills the gap in modern nonparametric statistical theory by discussing hypothesis testing and addresses mathematical statisticians who are interesting in the theory of non-parametric statistical inference. It will be of interest to specialists who are dealing with applied non-parametric statistical problems relevant in signal detection and transmission and in technical and medical diagnostics among others.


Nonparametric Goodness-of-Fit Testing Under Gaussian Models Related Books

Nonparametric Goodness-of-Fit Testing Under Gaussian Models
Language: en
Pages: 471
Authors: Yuri Ingster
Categories: Mathematics
Type: BOOK - Published: 2012-11-12 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

This book presents the modern theory of nonparametric goodness-of-fit testing. It fills the gap in modern nonparametric statistical theory by discussing hypothe
Parametric and Nonparametric Inference from Record-Breaking Data
Language: en
Pages: 123
Authors: Sneh Gulati
Categories: Mathematics
Type: BOOK - Published: 2013-03-14 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

By providing a comprehensive look at statistical inference from record-breaking data in both parametric and nonparametric settings, this book treats the area of
Nonlinear Estimation and Classification
Language: en
Pages: 465
Authors: David D. Denison
Categories: Mathematics
Type: BOOK - Published: 2013-11-11 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

Researchers in many disciplines face the formidable task of analyzing massive amounts of high-dimensional and highly-structured data. This is due in part to rec
Foundations of Statistical Inference
Language: en
Pages: 227
Authors: Yoel Haitovsky
Categories: Mathematics
Type: BOOK - Published: 2012-12-06 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

This volume is a collection of papers presented at a conference held in Shoresh Holiday Resort near Jerusalem, Israel, in December 2000 organized by the Israeli
Block Designs: A Randomization Approach
Language: en
Pages: 364
Authors: Tadeusz Calinski
Categories: Mathematics
Type: BOOK - Published: 2012-12-06 - Publisher: Springer Science & Business Media

DOWNLOAD EBOOK

The book is composed of two volumes, each consisting of five chapters. In Vol ume I, following some statistical motivation based on a randomization model, a gen