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Higher order multivariate inference using approximation methods
Descriptive
TitleInfo
Title
Higher order multivariate inference using approximation methods
Name
(type = personal)
NamePart
(type = family)
Wu
NamePart
(type = given)
Yaoshi
NamePart
(type = date)
1975-
DisplayForm
Yaoshi Wu
Role
RoleTerm
(authority = RULIB)
author
Name
(type = personal)
NamePart
(type = family)
Kolassa
NamePart
(type = given)
John
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John Kolassa
Affiliation
Advisory Committee
Role
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(authority = RULIB)
chair
Name
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NamePart
Rutgers University
Role
RoleTerm
(authority = RULIB)
degree grantor
Name
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NamePart
Graduate School - New Brunswick
Role
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school
TypeOfResource
Text
Genre
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theses
OriginInfo
DateCreated
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2015
DateOther
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(type = degree)
2015-10
CopyrightDate
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(qualifier = exact)
2015
Place
PlaceTerm
(type = code)
xx
Language
LanguageTerm
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(type = code)
eng
Abstract
(type = abstract)
The bivariate con dence region of two parameters of interest conditioning on one nuisance parameter is evaluated to the error of Op(1/n) using Laplace's approximation. A joint matching prior in the Bayesian framework is developed using Laplace's approximation to establish a mathematical equivalence such that the posterior quartiles coincide with the con dence region de ned as in a frequency approach. Quadratic saddlepoint approximation is developed to evaluate bivariate conditional and unconditional tail probability to the error of Op( 1/n) using saddlepoint approximation. The quadratic saddlepoint approximation is extended to three dimension to evaluate trivariate unconditional tail probability.
Subject
(authority = RUETD)
Topic
Statistics and Biostatistics
RelatedItem
(type = host)
TitleInfo
Title
Rutgers University Electronic Theses and Dissertations
Identifier
(type = RULIB)
ETD
Identifier
ETD_6815
PhysicalDescription
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(authority = gmd)
electronic resource
InternetMediaType
application/pdf
InternetMediaType
text/xml
Extent
1 online resource (iv, 86 p. : ill.)
Note
(type = degree)
Ph.D.
Note
(type = bibliography)
Includes bibliographical references
Subject
(authority = ETD-LCSH)
Topic
Method of steepest descent (Numerical analysis)
Subject
(authority = ETD-LCSH)
Topic
Approximation theory
Note
(type = statement of responsibility)
by Yaoshi Wu
RelatedItem
(type = host)
TitleInfo
Title
Graduate School - New Brunswick Electronic Theses and Dissertations
Identifier
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rucore19991600001
Location
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(displayLabel = Rutgers, The State University of New Jersey)
NjNbRU
Identifier
(type = doi)
doi:10.7282/T3TF00BH
Genre
(authority = ExL-Esploro)
ETD doctoral
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Rights
RightsDeclaration
(ID = rulibRdec0006)
The author owns the copyright to this work.
RightsHolder
(type = personal)
Name
FamilyName
Wu
GivenName
Yaoshi
Role
Copyright Holder
RightsEvent
Type
Permission or license
DateTime
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(qualifier = exact);
(point = start)
2015-09-29 09:56:43
AssociatedEntity
Name
Yaoshi Wu
Role
Copyright holder
Affiliation
Rutgers University. Graduate School - New Brunswick
AssociatedObject
Type
License
Name
Author Agreement License
Detail
I hereby grant to the Rutgers University Libraries and to my school the non-exclusive right to archive, reproduce and distribute my thesis or dissertation, in whole or in part, and/or my abstract, in whole or in part, in and from an electronic format, subject to the release date subsequently stipulated in this submittal form and approved by my school. I represent and stipulate that the thesis or dissertation and its abstract are my original work, that they do not infringe or violate any rights of others, and that I make these grants as the sole owner of the rights to my thesis or dissertation and its abstract. I represent that I have obtained written permissions, when necessary, from the owner(s) of each third party copyrighted matter to be included in my thesis or dissertation and will supply copies of such upon request by my school. I acknowledge that RU ETD and my school will not distribute my thesis or dissertation or its abstract if, in their reasonable judgment, they believe all such rights have not been secured. I acknowledge that I retain ownership rights to the copyright of my work. I also retain the right to use all or part of this thesis or dissertation in future works, such as articles or books.
Copyright
Status
Copyright protected
Availability
Status
Open
Reason
Permission or license
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Technical
RULTechMD
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ContentModel
ETD
OperatingSystem
(VERSION = 5.1)
windows xp
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Statistical Profile