Editorial to special issue V WCDANM 2018
Main Author: | |
---|---|
Publication Date: | 2020 |
Other Authors: | , |
Format: | Article |
Language: | eng |
Source: | Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
Download full: | http://hdl.handle.net/10400.22/18668 |
Summary: | 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. |
id |
RCAP_cb4595d74ef9518b217d76f566323113 |
---|---|
oai_identifier_str |
oai:recipp.ipp.pt:10400.22/18668 |
network_acronym_str |
RCAP |
network_name_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository_id_str |
https://opendoar.ac.uk/repository/7160 |
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 |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10400.22/18668 |
url |
http://hdl.handle.net/10400.22/18668 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1080/02664763.2020.1818489 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Taylor & Francis |
publisher.none.fl_str_mv |
Taylor & Francis |
dc.source.none.fl_str_mv |
reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia instacron:RCAAP |
instname_str |
FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
instacron_str |
RCAAP |
institution |
RCAAP |
reponame_str |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
collection |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) |
repository.name.fl_str_mv |
Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia |
repository.mail.fl_str_mv |
info@rcaap.pt |
_version_ |
1833600758286647296 |