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U-statistics, Mm-estimators and resa...

Bose, Arup.

U-statistics, Mm-estimators and resampling

Record Type:	Electronic resources : Monograph/item
Title/Author:	U-statistics, Mm-estimators and resamplingby Arup Bose, Snigdhansu Chatterjee.
Author:	Bose, Arup.
other author:	Chatterjee, Snigdhansu.
Published:	Singapore :Springer Singapore :2018.
Description:	xv, 174 p. :ill., digital ;24 cm.
Contained By:	Springer eBooks
Subject:	Estimation theory.
Online resource:	https://doi.org/10.1007/978-981-13-2248-8
ISBN:	9789811322488$q(electronic bk.)

U-statistics, Mm-estimators and resampling
Bose, Arup.

U-statistics, Mm-estimators and resampling[electronic resource] /by Arup Bose, Snigdhansu Chatterjee. - Singapore :Springer Singapore :2018. - xv, 174 p. :ill., digital ;24 cm. - Texts and readings in mathematics,v.752366-8717 ;. - Texts and readings in mathematics ;74..

Chapter 1. Introduction to U-statistics -- Chapter 2. M-estimators and U-statistics -- Chapter 3. Introduction to resampling -- Chapter 4. Resampling U-statistics and M-estimators -- Chapter 5. An Introduction to R.

This is an introductory text on a broad class of statistical estimators that are minimizers of convex functions. It covers the basics of U-statistics and Mm-estimators and develops their asymptotic properties. It also provides an elementary introduction to resampling, particularly in the context of these estimators. The last chapter is on practical implementation of the methods presented in other chapters, using the free software R.

ISBN: 9789811322488$q(electronic bk.)

Standard No.: 10.1007/978-981-13-2248-8doiSubjects--Topical Terms:

181864
Estimation theory.

LC Class. No.: QA276.8 / .B674 2018

Dewey Class. No.: 519.5

U-statistics, Mm-estimators and resampling
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505 0 $a Chapter 1. Introduction to U-statistics -- Chapter 2. M-estimators and U-statistics -- Chapter 3. Introduction to resampling -- Chapter 4. Resampling U-statistics and M-estimators -- Chapter 5. An Introduction to R.
520 $a This is an introductory text on a broad class of statistical estimators that are minimizers of convex functions. It covers the basics of U-statistics and Mm-estimators and develops their asymptotic properties. It also provides an elementary introduction to resampling, particularly in the context of these estimators. The last chapter is on practical implementation of the methods presented in other chapters, using the free software R.
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