Publication: Energy Performance Evaluation of OECD Countries Using Bayesian Stochastic Frontier Analysis and Bayesian Network Classifiers
| dc.authorscopusid | 12766595200 | |
| dc.authorscopusid | 57191925575 | |
| dc.authorscopusid | 36126813200 | |
| dc.contributor.author | Cengiz, M.A. | |
| dc.contributor.author | Dunder, E. | |
| dc.contributor.author | Şenel, T. | |
| dc.date.accessioned | 2020-06-21T13:17:43Z | |
| dc.date.available | 2020-06-21T13:17:43Z | |
| dc.date.issued | 2018 | |
| dc.department | Ondokuz Mayıs Üniversitesi | en_US |
| dc.department-temp | [Cengiz] Mehmet Ali, Department of Statistics, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Dunder] Emre, Department of Statistics, Ondokuz Mayis Üniversitesi, Samsun, Turkey; [Şenel] Talat, Department of Statistics, Ondokuz Mayis Üniversitesi, Samsun, Turkey | en_US |
| dc.description.abstract | More recently a large amount of interest has been devoted to the use of Bayesian methods for deriving parameter estimates of the stochastic frontier analysis. Bayesian stochastic frontier analysis (BSFA) seems to be a useful method to assess the efficiency in energy sector. However, BSFA results do not expose the multiple relationships between input and output variables and energy efficiency. This study proposes a framework to make inferences about BSFA efficiencies, recognizing the underlying relationships between variables and efficiency, using Bayesian network (BN) approach. BN classifiers are proposed as a method to analyze the results obtained from BSFA. © 2017 Informa UK Limited, trading as Taylor & Francis Group. | en_US |
| dc.identifier.doi | 10.1080/02664763.2016.1257586 | |
| dc.identifier.endpage | 25 | en_US |
| dc.identifier.issn | 0266-4763 | |
| dc.identifier.issn | 1360-0532 | |
| dc.identifier.issue | 1 | en_US |
| dc.identifier.scopus | 2-s2.0-85008624404 | |
| dc.identifier.scopusquality | Q2 | |
| dc.identifier.startpage | 17 | en_US |
| dc.identifier.uri | https://doi.org/10.1080/02664763.2016.1257586 | |
| dc.identifier.volume | 45 | en_US |
| dc.identifier.wos | WOS:000415929600003 | |
| dc.identifier.wosquality | Q3 | |
| dc.language.iso | en | en_US |
| dc.publisher | Taylor and Francis Ltd. michael.wagreich@univie.ac.at | en_US |
| dc.relation.ispartof | Journal of Applied Statistics | en_US |
| dc.relation.journal | Journal of Applied Statistics | en_US |
| dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Bayesian | en_US |
| dc.subject | Bayesian Network | en_US |
| dc.subject | Energy | en_US |
| dc.subject | Stochastic Frontier Analysis | en_US |
| dc.title | Energy Performance Evaluation of OECD Countries Using Bayesian Stochastic Frontier Analysis and Bayesian Network Classifiers | en_US |
| dc.type | Article | en_US |
| dspace.entity.type | Publication |
