Publication
Editorial to special issue V WCDANM 2018
| dc.contributor.author | Stehlík, M. | |
| dc.contributor.author | Grilo, L. M. | |
| dc.contributor.author | Jordanova, P. K. | |
| dc.date.accessioned | 2021-10-07T09:44:45Z | |
| dc.date.available | 2021-10-07T09:44:45Z | |
| dc.date.issued | 2020 | |
| dc.description.abstract | The special issue Advances in Computational Data Analysis of the Journal of Applied Statistics (JAS), Taylor & Francis, contains mainly papers that were presented in the fifth Annual Workshop of Computational Data Analysis and Numerical Methods (V WCDANM), which took place on 11–12 May 2018, at the Polytechnic Institute of Porto, Portugal. The organizing committee of V WCDANM – 2018, with the support of the Polytechnic Institute of Tomar and the University of Évora, developed a program that includes prominent keynote speakers and a high scientific level of oral and poster sessions, with participants from Portugal and abroad. Theoretical and applied works in different research fields were presented, namely in health and social sciences, environmental science, economics and engineering (some involving data science, data mining, big data and machine learning). A considerable number of manuscripts were submitted to this special issue and more than 30 papers, after carefully reviewed by referees, were accepted and are distributed in three issues of JAS Volume 47. The selected papers offer readers the opportunity to access different statistical approaches, as well as to view a wide range of application areas. These research works provide the appropriate framework and background for real-life problems and also they reflect a comprehensive view of different statistical fields, promoting links with a variety of related disciplines, exploring computational issues and presenting some future research trends. | pt_PT |
| dc.description.sponsorship | This work was also supported by the Bulgarian National Science Funds under the bilateral projects Bulgaria – Austria, 2016–2019, Feasible statistical modeling for extremes in ecology and finance, Contract number 01/8, 23/08/2017 and WTZ Project BG 09/2017. | pt_PT |
| dc.description.version | info:eu-repo/semantics/publishedVersion | pt_PT |
| dc.identifier.doi | 10.1080/02664763.2020.1818489 | pt_PT |
| dc.identifier.uri | http://hdl.handle.net/10400.22/18668 | |
| dc.language.iso | eng | pt_PT |
| dc.publisher | Taylor & Francis | pt_PT |
| dc.relation.publisherversion | https://www.tandfonline.com/doi/full/10.1080/02664763.2020.1818489 | pt_PT |
| dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | pt_PT |
| dc.subject | Annual Workshop of Computational Data Analysis and Numerical Methods | pt_PT |
| dc.subject | V WCDANM | pt_PT |
| dc.title | Editorial to special issue V WCDANM 2018 | pt_PT |
| dc.type | journal article | |
| dspace.entity.type | Publication | |
| oaire.citation.endPage | 2298 | pt_PT |
| oaire.citation.issue | 13-15 | pt_PT |
| oaire.citation.startPage | 2289 | pt_PT |
| oaire.citation.title | Journal of Applied Statistics | pt_PT |
| oaire.citation.volume | 47 | pt_PT |
| rcaap.rights | openAccess | pt_PT |
| rcaap.type | article | pt_PT |
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