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Estimation and Inference of Directio...
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Fang, Zheng.
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Estimation and Inference of Directionally Differentiable Functions: Theory and Applications.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Estimation and Inference of Directionally Differentiable Functions: Theory and Applications./
Author:
Fang, Zheng.
Description:
183 p.
Notes:
Source: Dissertation Abstracts International, Volume: 76-11(E), Section: A.
Contained By:
Dissertation Abstracts International76-11A(E).
Subject:
Economics. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3709616
ISBN:
9781321852509
Estimation and Inference of Directionally Differentiable Functions: Theory and Applications.
Fang, Zheng.
Estimation and Inference of Directionally Differentiable Functions: Theory and Applications.
- 183 p.
Source: Dissertation Abstracts International, Volume: 76-11(E), Section: A.
Thesis (Ph.D.)--University of California, San Diego, 2015.
This dissertation addresses a large class of irregular models in economics and statistics -- settings in which the parameters of interest take the form &phis;(theta 0), where &phis; is a known directionally differentiable function and theta 0 is estimated by thetan. Chapter 1 provides a tractable framework for conducting inference, Chapter 2 focuses on optimality of estimation, and Chapter 3 applies the developed theory to construct a test whether a Hilbert space valued parameter belongs to a convex set and to derive the uniform weak convergence of the Grenander distribution function -- i.e. the least concave majorant of the empirical distribution function -- under minimal assumptions.
ISBN: 9781321852509Subjects--Topical Terms:
517137
Economics.
Estimation and Inference of Directionally Differentiable Functions: Theory and Applications.
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Estimation and Inference of Directionally Differentiable Functions: Theory and Applications.
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183 p.
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Source: Dissertation Abstracts International, Volume: 76-11(E), Section: A.
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Adviser: Andres Santos.
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Thesis (Ph.D.)--University of California, San Diego, 2015.
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This dissertation addresses a large class of irregular models in economics and statistics -- settings in which the parameters of interest take the form &phis;(theta 0), where &phis; is a known directionally differentiable function and theta 0 is estimated by thetan. Chapter 1 provides a tractable framework for conducting inference, Chapter 2 focuses on optimality of estimation, and Chapter 3 applies the developed theory to construct a test whether a Hilbert space valued parameter belongs to a convex set and to derive the uniform weak convergence of the Grenander distribution function -- i.e. the least concave majorant of the empirical distribution function -- under minimal assumptions.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3709616
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