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DC Field | Value | Language |
---|---|---|
dc.contributor.author | Woraphon Yamaka | en_US |
dc.date.accessioned | 2022-05-27T08:29:34Z | - |
dc.date.available | 2022-05-27T08:29:34Z | - |
dc.date.issued | 2022-01-01 | en_US |
dc.identifier.issn | 18609503 | en_US |
dc.identifier.issn | 1860949X | en_US |
dc.identifier.other | 2-s2.0-85113373680 | en_US |
dc.identifier.other | 10.1007/978-3-030-77094-5_11 | en_US |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85113373680&origin=inward | en_US |
dc.identifier.uri | http://cmuir.cmu.ac.th/jspui/handle/6653943832/72787 | - |
dc.description.abstract | In this study, we propose a copula-based stochastic production frontier efficiency effects model. This model estimates the inefficiency scores and exogenous effects in one single step. As the conventional model contains two independent error components with one representing the inefficiency effects and the other assuming the random normal errors, we are concerned about the independence error terms assumption in the conventional approach. Thus, we relax this assumption and join the two errors through copula function. The model is investigated for its performance using the simulation and real data sets. The results show the accuracy and higher performance of our model when compared to the classical model specifications. | en_US |
dc.subject | Computer Science | en_US |
dc.title | Efficiency Effects in a Copula Based Stochastic Frontier Model | en_US |
dc.type | Book Series | en_US |
article.title.sourcetitle | Studies in Computational Intelligence | en_US |
article.volume | 983 | en_US |
article.stream.affiliations | Chiang Mai University | en_US |
Appears in Collections: | CMUL: Journal Articles |
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