Special issue on statistical analysis of networks: Preface by the guest editors

The special issue on Statistical Analysis of Networks aspires to convey the breadth and depth of statistical learning with networks, ranging from networks that are observed to networks that are unobserved and learned from data. It includes ten select papers with methodological and theoretical advanc...

Descripción completa

Detalles Bibliográficos
Autores principales: Schweinberger, Michael, Stingo, Francesco C., Vitale, Maria Prosperina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8576455/
https://www.ncbi.nlm.nih.gov/pubmed/34776825
http://dx.doi.org/10.1007/s10260-021-00608-z
_version_ 1784595879141834752
author Schweinberger, Michael
Stingo, Francesco C.
Vitale, Maria Prosperina
author_facet Schweinberger, Michael
Stingo, Francesco C.
Vitale, Maria Prosperina
author_sort Schweinberger, Michael
collection PubMed
description The special issue on Statistical Analysis of Networks aspires to convey the breadth and depth of statistical learning with networks, ranging from networks that are observed to networks that are unobserved and learned from data. It includes ten select papers with methodological and theoretical advances, and demonstrates the usefulness of the network paradigm by applications to current problems.
format Online
Article
Text
id pubmed-8576455
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Springer Berlin Heidelberg
record_format MEDLINE/PubMed
spelling pubmed-85764552021-11-09 Special issue on statistical analysis of networks: Preface by the guest editors Schweinberger, Michael Stingo, Francesco C. Vitale, Maria Prosperina Stat Methods Appt Article The special issue on Statistical Analysis of Networks aspires to convey the breadth and depth of statistical learning with networks, ranging from networks that are observed to networks that are unobserved and learned from data. It includes ten select papers with methodological and theoretical advances, and demonstrates the usefulness of the network paradigm by applications to current problems. Springer Berlin Heidelberg 2021-11-09 2021 /pmc/articles/PMC8576455/ /pubmed/34776825 http://dx.doi.org/10.1007/s10260-021-00608-z Text en © Springer-Verlag GmbH Germany, part of Springer Nature 2021 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Schweinberger, Michael
Stingo, Francesco C.
Vitale, Maria Prosperina
Special issue on statistical analysis of networks: Preface by the guest editors
title Special issue on statistical analysis of networks: Preface by the guest editors
title_full Special issue on statistical analysis of networks: Preface by the guest editors
title_fullStr Special issue on statistical analysis of networks: Preface by the guest editors
title_full_unstemmed Special issue on statistical analysis of networks: Preface by the guest editors
title_short Special issue on statistical analysis of networks: Preface by the guest editors
title_sort special issue on statistical analysis of networks: preface by the guest editors
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8576455/
https://www.ncbi.nlm.nih.gov/pubmed/34776825
http://dx.doi.org/10.1007/s10260-021-00608-z
work_keys_str_mv AT schweinbergermichael specialissueonstatisticalanalysisofnetworksprefacebytheguesteditors
AT stingofrancescoc specialissueonstatisticalanalysisofnetworksprefacebytheguesteditors
AT vitalemariaprosperina specialissueonstatisticalanalysisofnetworksprefacebytheguesteditors

Ejemplares similares