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dc.contributor.authorRungrapee Phadkanthaen_US
dc.contributor.authorWoraphon Yamakaen_US
dc.contributor.authorSongsak Sriboonchittaen_US
dc.description.abstractThe purpose of this paper is to introduce an approach to fitting a quantile regression on interval-valued data. This approach consists of fitting a model on the appropriate point of the interval values. To obtain this point, the convex combination method is applied in the quantile regression. Moreover, we also introduce the Bayesian approach for estimating all the unknown parameters in the model. The approach is illustrated via a simulation study and real data sets. In the real data study, we apply this methodology to measure the beta risk of Thai stock returns through Capital Asset Pricing model. The results show the high performance and accuracy of the Bayesian estimation in both simulated data and real application study.en_US
dc.subjectComputer Scienceen_US
dc.subjectDecision Sciencesen_US
dc.subjectEconomics, Econometrics and Financeen_US
dc.titleA Bayesian Approach to Quantile Regression for Interval-Valued Data: Application to CAPMen_US
dc.typeBook Seriesen_US
article.title.sourcetitleStudies in Systems, Decision and Controlen_US
article.volume429en_US Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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