Please use this identifier to cite or link to this item: https://doi.org/10.1111/j.1467-842X.2006.00443.x
DC FieldValue
dc.titleAn exclusive regressors binary mixture model with an application to labour supply
dc.contributor.authorLu, Z.-H.
dc.contributor.authorBrown, B.M.
dc.date.accessioned2016-11-08T08:25:20Z
dc.date.available2016-11-08T08:25:20Z
dc.date.issued2006-09
dc.identifier.citationLu, Z.-H., Brown, B.M. (2006-09). An exclusive regressors binary mixture model with an application to labour supply. Australian and New Zealand Journal of Statistics 48 (3) : 321-333. ScholarBank@NUS Repository. https://doi.org/10.1111/j.1467-842X.2006.00443.x
dc.identifier.issn13691473
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/129681
dc.description.abstractThis paper suggests a new type of mixture regression model, in which each mixture component is explained by its own regressors. Thus, the dependent variable can be driven by one of several unobservable explanatory mechanisms, each of which has its own distinct variables. An extension of the simulated annealing algorithm is introduced to fit this general mixture model. The paper also suggests a new technique for estimating the covariance matrix of estimators in a mixture model. Finally, empirical studies of a labour supply example show that our proposed model can perform much better than conventional logistic or mixture models. © 2006 Australian Statistical Publishing Association Inc.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1111/j.1467-842X.2006.00443.x
dc.sourceScopus
dc.subjectBayesian information criterion (BIC)
dc.subjectConstrained maximum likelihood
dc.subjectLocal optima
dc.subjectLogistic regression
dc.subjectParameter identifiability
dc.typeArticle
dc.contributor.departmentSTATISTICS & APPLIED PROBABILITY
dc.description.doi10.1111/j.1467-842X.2006.00443.x
dc.description.sourcetitleAustralian and New Zealand Journal of Statistics
dc.description.volume48
dc.description.issue3
dc.description.page321-333
dc.identifier.isiut000240915500004
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