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On variance estimation and a goodness-of-fit test using the bootstrap method

Amiri, Saeid (2009). On variance estimation and a goodness-of-fit test using the bootstrap method. Uppsala : Sveriges lantbruksuniv. , Rapport / Institutionen för energi och teknik, SLU, 1654-9406 ; 007
ISBN 978-91-86197-20-9
[Licentiate thesis]

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Abstract

This thesis deals with the study of variance estimation using the bootstrap method, including the problem of choosing between nonparametric and parametric bootstrap methods. Paper I compares the two approaches, determines which method is preferable and analyses the accuracy of the approximations. The underlying concept of parametric bootstrap is based on the assumption of correct choice of parametric distribution. Paper II therefore considers goodness-of-fit tests and presents a new test based on the bootstrap method.

Authors/Creators:Amiri, Saeid
Title:On variance estimation and a goodness-of-fit test using the bootstrap method
Series/Journal:Rapport / Institutionen för energi och teknik, SLU (1654-9406)
Year of publishing :2009
Volume:007
Number of Pages:28
Papers/manuscripts:
NumberReferences
I.A comparison of bootstrap methods for variance estimation Report no 2009:02 Centre of Biostochastics. Swedish University of Agriculture Sciences
II.On a generalization of the Jarque-Bera test using the bootstrap method Report no 2009:03 Centre of Biostochastics. Swedish University of Agriculture Sciences
Place of Publication:Uppsala
Publisher:Department of Energy and Technology, Swedish University of Agricultural Sciences
ISBN for printed version:978-91-86197-20-9
ISSN:1654-9406
Language:English
Publication Type:Licentiate thesis
Full Text Status:Public
Agris subject categories.:X Agricola extesions > X10 Mathematics and statistics
Subjects:(A) Swedish standard research categories 2011 > 1 Natural sciences > 101 Mathematics > 10106 Probability Theory and Statistics
Agrovoc terms:statistical methods
Keywords:Nonparametric bootstrap, Parametric bootstrap, Goodness-of-fit test, Variance
URN:NBN:urn:nbn:se:slu:epsilon-2880
Permanent URL:
http://urn.kb.se/resolve?urn=urn:nbn:se:slu:epsilon-2880
ID Code:2015
Faculty:NL - Faculty of Natural Resources and Agricultural Sciences (until 2013)
Department:(NL, NJ) > Dept. of Energy and Technology
Deposited By: saeid amiri
Deposited On:20 May 2009 00:00
Metadata Last Modified:08 Sep 2017 11:01

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