Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/57048
Title: Frontier quantile model using a generalized class of skewed distributions
Authors: Varith Pipitpojanakarn
Woraphon Yamaka
Songsak Sriboonchitta
Paravee Maneejuk
Keywords: Computer Science
Energy
Engineering
Environmental Science
Mathematics
Social Sciences
Issue Date: 1-Nov-2017
Abstract: © 2017 American Scientific Publishers All rights reserved. One of the classical ways to predict manufacturing production is to use Stochastic frontier model. At present, the most accurate predictions obtained by using this model involve the use of quantiles and asymmetric Laplace distributions for the noise and inefficiency. In this paper, we analyze the possibility of using more general skew distributions. We show that skew normal distributions lead to better predictions.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85040913141&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/57048
ISSN: 19367317
19366612
Appears in Collections:CMUL: Journal Articles

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