Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/58538
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dc.contributor.authorVarith Pipitpojanakarnen_US
dc.contributor.authorParavee Maneejuken_US
dc.contributor.authorWorapon Yamakaen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.date.accessioned2018-09-05T04:26:02Z-
dc.date.available2018-09-05T04:26:02Z-
dc.date.issued2018-01-01en_US
dc.identifier.issn1860949Xen_US
dc.identifier.other2-s2.0-85038866490en_US
dc.identifier.other10.1007/978-3-319-73150-6_63en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85038866490&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/58538-
dc.description.abstract© 2018, Springer International Publishing AG. In this study, we propose a non-linear model for explaining the relationship between the dependent and the independent variables beyond the conditional mean. We extend the kink approach to expectile regression thus the model provides a more flexible means to explain the non-linear relationship in the model across different expectile indices. We also introduce the sup-F statistic test for the existence of kink effect in each expectile. The simulation and application studies are also proposed to examine the performance of our model. We apply our methodology to study the input factor affecting service sector growth in Asian economy. The use of this model allows us to identify and explore the non-linear labour effect on the service output. We can find both labour effect and kink effect present over a range of expectiles in the service output in this application.en_US
dc.subjectComputer Scienceen_US
dc.titleExpectile kink regression: An application to service sector outputen_US
dc.typeBook Seriesen_US
article.title.sourcetitleStudies in Computational Intelligenceen_US
article.volume760en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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