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Article: New expectation-maximization-type algorithms via stochastic representation for the analysis of truncated normal data with applications in biomedicine

TitleNew expectation-maximization-type algorithms via stochastic representation for the analysis of truncated normal data with applications in biomedicine
Authors
Tian, GJU, DYuen, KCZHANG, C
KeywordsAIC
BIC
bootstrap method
complementary random variable
EM algorithm
stochastic representation
truncated normal distribution
Issue Date2018
PublisherSage Publications Ltd. The Journal's web site is located at http://smm.sagepub.com
Citation
Statistical Methods in Medical Research, 2018, v. 27 n. 8, p. 2459-2477 How to Cite?
DOI: http://dx.doi.org/10.1177/0962280216681598
Persistent Identifierhttp://hdl.handle.net/10722/249690
ISSN
0962-2802
2021 Impact Factor: 2.494
2020 SCImago Journal Rankings: 1.952
ISI Accession Number ID
WOS:000438616300016

 

DC FieldValueLanguage
dc.contributor.authorTian, G-
dc.contributor.authorJU, D-
dc.contributor.authorYuen, KC-
dc.contributor.authorZHANG, C-
dc.date.accessioned2017-11-21T03:05:39Z-
dc.date.available2017-11-21T03:05:39Z-
dc.date.issued2018-
dc.identifier.citationStatistical Methods in Medical Research, 2018, v. 27 n. 8, p. 2459-2477-
dc.identifier.issn0962-2802-
dc.identifier.urihttp://hdl.handle.net/10722/249690-
dc.languageeng-
dc.publisherSage Publications Ltd. The Journal's web site is located at http://smm.sagepub.com-
dc.relation.ispartofStatistical Methods in Medical Research-
dc.rightsStatistical Methods in Medical Research. Copyright © Sage Publications Ltd.-
dc.subjectAIC-
dc.subjectBIC-
dc.subjectbootstrap method-
dc.subjectcomplementary random variable-
dc.subjectEM algorithm-
dc.subjectstochastic representation-
dc.subjecttruncated normal distribution-
dc.titleNew expectation-maximization-type algorithms via stochastic representation for the analysis of truncated normal data with applications in biomedicine-
dc.typeArticle-
dc.identifier.emailTian, G: gltian@hku.hk-
dc.identifier.emailYuen, KC: kcyuen@hku.hk-
dc.identifier.authorityTian, G=rp00789-
dc.identifier.authorityYuen, KC=rp00836-
dc.identifier.doi10.1177/0962280216681598-
dc.identifier.scopuseid_2-s2.0-85049883490-
dc.identifier.hkuros283120-
dc.identifier.volume27-
dc.identifier.issue8-
dc.identifier.spage2459-
dc.identifier.epage2477-
dc.identifier.isiWOS:000438616300016-
dc.publisher.placeUnited Kingdom-
dc.identifier.issnl0962-2802-

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