196 resultados para SIGHT VELOCITY DISTRIBUTIONS
Filtro por publicador
- Abertay Research Collections - Abertay University’s repository (1)
- Aberystwyth University Repository - Reino Unido (5)
- Academic Archive On-line (Stockholm University; Sweden) (1)
- Acceda, el repositorio institucional de la Universidad de Las Palmas de Gran Canaria. España (1)
- AMS Tesi di Dottorato - Alm@DL - Università di Bologna (1)
- AMS Tesi di Laurea - Alm@DL - Università di Bologna (1)
- Aquatic Commons (25)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (1)
- Aston University Research Archive (3)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (1)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (4)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (6)
- Boston University Digital Common (4)
- Brock University, Canada (5)
- Bucknell University Digital Commons - Pensilvania - USA (1)
- CaltechTHESIS (13)
- Cambridge University Engineering Department Publications Database (126)
- CentAUR: Central Archive University of Reading - UK (10)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (181)
- Cochin University of Science & Technology (CUSAT), India (15)
- CORA - Cork Open Research Archive - University College Cork - Ireland (1)
- DI-fusion - The institutional repository of Université Libre de Bruxelles (4)
- Diposit Digital de la UB - Universidade de Barcelona (1)
- DRUM (Digital Repository at the University of Maryland) (2)
- Duke University (6)
- eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry (3)
- Gallica, Bibliotheque Numerique - Bibliothèque nationale de France (French National Library) (BnF), France (15)
- Greenwich Academic Literature Archive - UK (9)
- Helda - Digital Repository of University of Helsinki (9)
- Illinois Digital Environment for Access to Learning and Scholarship Repository (1)
- Indian Institute of Science - Bangalore - Índia (134)
- Infoteca EMBRAPA (1)
- Instituto Politécnico do Porto, Portugal (6)
- Massachusetts Institute of Technology (1)
- Ministerio de Cultura, Spain (2)
- Plymouth Marine Science Electronic Archive (PlyMSEA) (48)
- Publishing Network for Geoscientific & Environmental Data (3)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (196)
- Queensland University of Technology - ePrints Archive (95)
- REPOSITORIO DIGITAL IMARPE - INSTITUTO DEL MAR DEL PERÚ, Peru (1)
- Repositório Institucional da Universidade de Aveiro - Portugal (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (3)
- Research Open Access Repository of the University of East London. (1)
- SAPIENTIA - Universidade do Algarve - Portugal (1)
- Universidade Complutense de Madrid (1)
- Universidade Federal do Rio Grande do Norte (UFRN) (2)
- Universitat de Girona, Spain (6)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (1)
- Université de Lausanne, Switzerland (3)
- Université de Montréal, Canada (18)
- University of Michigan (5)
- University of Queensland eSpace - Australia (3)
- University of Southampton, United Kingdom (1)
- University of Washington (1)
- Worcester Research and Publications - Worcester Research and Publications - UK (4)
Resumo:
Degree distribution is a fundamental property of networks. While mean degree provides a standard measure of scale, there are several commonly used shape measures. Widespread use of a single shape measure would enable comparisons between networks and facilitate investigations about the relationship between degree distribution properties and other network features. This paper describes five candidate measures of heterogeneity and recommends the Gini coefficient. It has theoretical advantages over many of the previously proposed measures, is meaningful for the broad range of distribution shapes seen in different types of networks, and has several accessible interpretations. While this paper focusses on degree, the distribution of other node based network properties could also be described with Gini coefficients.