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Contributions to the statistical inf...
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Zhao, Yue.
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Contributions to the statistical inference for the semiparametric elliptical copula model.
Record Type:
Electronic resources : Monograph/item
Title/Author:
Contributions to the statistical inference for the semiparametric elliptical copula model./
Author:
Zhao, Yue.
Description:
191 p.
Notes:
Source: Dissertation Abstracts International, Volume: 77-03(E), Section: A.
Contained By:
Dissertation Abstracts International77-03A(E).
Subject:
Technical communication. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3730486
ISBN:
9781339167541
Contributions to the statistical inference for the semiparametric elliptical copula model.
Zhao, Yue.
Contributions to the statistical inference for the semiparametric elliptical copula model.
- 191 p.
Source: Dissertation Abstracts International, Volume: 77-03(E), Section: A.
Thesis (Ph.D.)--Cornell University, 2015.
This thesis addresses aspects of the statistical inference problem for the semiparametric elliptical copula model. A copula (function) for a continuous multivariate distribution is the joint distribution function of the transformed marginal distributions, where the transformation is the probability integral transform. As such, copula is a tool to couple or decouple the multivariate dependence structure from the behaviors of the individual margins. (Abstract shortened by UMI.).
ISBN: 9781339167541Subjects--Topical Terms:
3172863
Technical communication.
Contributions to the statistical inference for the semiparametric elliptical copula model.
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Contributions to the statistical inference for the semiparametric elliptical copula model.
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191 p.
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Source: Dissertation Abstracts International, Volume: 77-03(E), Section: A.
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Adviser: Marten Wegkamp.
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Thesis (Ph.D.)--Cornell University, 2015.
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This thesis addresses aspects of the statistical inference problem for the semiparametric elliptical copula model. A copula (function) for a continuous multivariate distribution is the joint distribution function of the transformed marginal distributions, where the transformation is the probability integral transform. As such, copula is a tool to couple or decouple the multivariate dependence structure from the behaviors of the individual margins. (Abstract shortened by UMI.).
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School code: 0058.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3730486
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