View : 849 Download: 0

Full metadata record

DC Field Value Language
dc.contributor.author신동완*
dc.date.accessioned2021-02-25T16:31:16Z-
dc.date.available2021-02-25T16:31:16Z-
dc.date.issued2020*
dc.identifier.issn1226-3192*
dc.identifier.issn2005-2863*
dc.identifier.otherOAK-27957*
dc.identifier.urihttps://dspace.ewha.ac.kr/handle/2015.oak/257063-
dc.description.abstractWe consider block bootstrappings for panel mean change test of the squared CUSUM test of Horvath and Huskova (J Time Ser Anal 33:631-648, 2012): the circular block bootstrapping and stationary bootstrapping. First order asymptotic null validity of the test is proved under serial and/or cross-sectional correlation. Consistency of the test under an alternative hypothesis is also proved. A Monte-Carlo experiment reveals that the existing tests of Horvath and Huskova (2012) and others have severe size distortions for serially and/or cross-sectionally correlated panels, and the block bootstrappings remedy this size distortion problem. A real data analysis illustrates the proposed method.*
dc.languageEnglish*
dc.publisherSPRINGER HEIDELBERG*
dc.subjectBootstrap test*
dc.subjectPanel mean break*
dc.subjectCross-sectional dependence*
dc.subjectSerial dependence*
dc.subjectCircular block bootstrapping*
dc.subjectStationary bootstrapping*
dc.titleBlock bootstrapping for a panel mean break test*
dc.typeArticle*
dc.relation.issue3*
dc.relation.volume49*
dc.relation.indexSCIE*
dc.relation.indexSCOPUS*
dc.relation.indexKCI*
dc.relation.startpage802*
dc.relation.lastpage821*
dc.relation.journaltitleJOURNAL OF THE KOREAN STATISTICAL SOCIETY*
dc.identifier.doi10.1007/s42952-019-00034-8*
dc.identifier.wosidWOS:000522858200008*
dc.identifier.scopusid2-s2.0-85079598086*
dc.author.googleChoi, Ji-Eun*
dc.author.googleShin, Dong Wan*
dc.contributor.scopusid신동완(7403352539)*
dc.date.modifydate20240116115756*
Appears in Collections:
자연과학대학 > 통계학전공 > Journal papers
Files in This Item:
There are no files associated with this item.
Export
RIS (EndNote)
XLS (Excel)
XML


qrcode

BROWSE