Editorial to special issue V WCDANM 2018

Detalhes bibliográficos
Autor(a) principal: Stehlík, M.
Data de Publicação: 2020
Outros Autores: Grilo, L. M., Jordanova, P. K.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10400.22/18668
Resumo: 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.
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spelling Editorial to special issue V WCDANM 2018Annual Workshop of Computational Data Analysis and Numerical MethodsV WCDANMThe 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.Taylor & FrancisREPOSITÓRIO P.PORTOStehlík, M.Grilo, L. M.Jordanova, P. K.2021-10-07T09:44:45Z20202020-01-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10400.22/18668eng10.1080/02664763.2020.1818489info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-07T10:27:34Zoai:recipp.ipp.pt:10400.22/18668Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T00:55:39.265142Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Editorial to special issue V WCDANM 2018
title Editorial to special issue V WCDANM 2018
spellingShingle Editorial to special issue V WCDANM 2018
Stehlík, M.
Annual Workshop of Computational Data Analysis and Numerical Methods
V WCDANM
title_short Editorial to special issue V WCDANM 2018
title_full Editorial to special issue V WCDANM 2018
title_fullStr Editorial to special issue V WCDANM 2018
title_full_unstemmed Editorial to special issue V WCDANM 2018
title_sort Editorial to special issue V WCDANM 2018
author Stehlík, M.
author_facet Stehlík, M.
Grilo, L. M.
Jordanova, P. K.
author_role author
author2 Grilo, L. M.
Jordanova, P. K.
author2_role author
author
dc.contributor.none.fl_str_mv REPOSITÓRIO P.PORTO
dc.contributor.author.fl_str_mv Stehlík, M.
Grilo, L. M.
Jordanova, P. K.
dc.subject.por.fl_str_mv Annual Workshop of Computational Data Analysis and Numerical Methods
V WCDANM
topic Annual Workshop of Computational Data Analysis and Numerical Methods
V WCDANM
description 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.
publishDate 2020
dc.date.none.fl_str_mv 2020
2020-01-01T00:00:00Z
2021-10-07T09:44:45Z
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dc.relation.none.fl_str_mv 10.1080/02664763.2020.1818489
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