Nonparametric estimation under shape constraints : estimators, algorithms, and asymptotics / Piet Groeneboom and Geurt Jongbloed.

By:

Groeneboom, Piet

Contributor(s):

Jongbloed, Geurt

Material type: Text

TextSeries: Cambridge series in statistical and probabilistic mathematicsPublication details: New York : Cambridge University Press, 2014.Description: xi, 416 p. : illustrations ; 27 cmISBN:

9780521864015 (hbk.)

Subject(s):

DDC classification:

000SA.12 23 G874

Contents:

1. Introduction; 2. Basic estimation problems with monotonicity constraints; 3. Asymptotic theory for the basic monotone problems; 4. Other univariate problems involving monotonicity constraints; 5. Higher dimensional problems; 6. Lower bounds on estimation rates; 7. Algorithms and computation; 8. Shape and smoothness; 9. Testing and confidence intervals; 10. Asymptotic theory of smooth functionals; 11. Pointwise asymptotic distribution theory for univariate problems; 12. Pointwise asymptotic distribution theory for multivariate problems; 13. Asymptotic distribution of global deviations; References; Author index; Subject index.

Summary: This book introduces basic concepts of shape constrained inference and guides the reader to current developments in the subject.

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Item type	Current library	Call number	Status	Date due	Barcode	Item holds
Books	ISI Library, Kolkata	000SA.12 G874 (Browse shelf(Opens below))	Available		136304

Total holds: 0

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Previous	000SA.1 Sa163 Inference on time-to-event distribution from retrospective data with imperfect recall /	000SA.12 C435 Nonparametric methods for data in infinite dimensional space /	000SA.12 D456 Nonparametric statistics :	000SA.12 G874 Nonparametric estimation under shape constraints : estimators, algorithms, and asymptotics /	000SA.12 H737 Nonparametric statistical methods.	000SA.12 H737 Nonparametric statistical methods.	000SA.12 J61 Nonparametric statistical methods and related topics :	Next

Includes bibliographical references (pages 401-408) and indexes.

1. Introduction;
2. Basic estimation problems with monotonicity constraints;
3. Asymptotic theory for the basic monotone problems;
4. Other univariate problems involving monotonicity constraints;
5. Higher dimensional problems;
6. Lower bounds on estimation rates;
7. Algorithms and computation;
8. Shape and smoothness;
9. Testing and confidence intervals;
10. Asymptotic theory of smooth functionals;
11. Pointwise asymptotic distribution theory for univariate problems;
12. Pointwise asymptotic distribution theory for multivariate problems;
13. Asymptotic distribution of global deviations;
References;
Author index;
Subject index.

This book introduces basic concepts of shape constrained inference and guides the reader to current developments in the subject.

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