Frontier quantile model using a generalized class of skewed distributions

Frontier quantile model using a generalized class of skewed distributions

© 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 t...

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Bibliographic Details
Main Authors: Varith Pipitpojanakarn, Woraphon Yamaka, Songsak Sriboonchitta, Paravee Maneejuk
Format: Journal
Published: 2018
Subjects:
Computer Science
Energy
Engineering
Environmental Science
Mathematics
Social Sciences
Online Access:https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85040913141&origin=inward
http://cmuir.cmu.ac.th/jspui/handle/6653943832/57048
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Institution: Chiang Mai University
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Summary:© 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.

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