1 resultado para DENDRITIC BRANCHING FEATURES
em Universitat de Girona, Spain
Filtro por publicador
- Aberystwyth University Repository - Reino Unido (2)
- Andina Digital - Repositorio UASB-Digital - Universidade Andina Simón Bolívar (1)
- Applied Math and Science Education Repository - Washington - USA (1)
- Aquatic Commons (16)
- ArchiMeD - Elektronische Publikationen der Universität Mainz - Alemanha (1)
- Archive of European Integration (1)
- Archivo Digital para la Docencia y la Investigación - Repositorio Institucional de la Universidad del País Vasco (7)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (1)
- Biblioteca Digital da Produção Intelectual da Universidade de São Paulo (BDPI/USP) (29)
- Biblioteca Digital de Teses e Dissertações Eletrônicas da UERJ (1)
- BORIS: Bern Open Repository and Information System - Berna - Suiça (1)
- Boston University Digital Common (1)
- Brock University, Canada (4)
- CaltechTHESIS (3)
- Cambridge University Engineering Department Publications Database (71)
- CentAUR: Central Archive University of Reading - UK (68)
- Centro Hospitalar do Porto (1)
- Chinese Academy of Sciences Institutional Repositories Grid Portal (94)
- Cochin University of Science & Technology (CUSAT), India (15)
- CORA - Cork Open Research Archive - University College Cork - Ireland (1)
- Dalarna University College Electronic Archive (6)
- DI-fusion - The institutional repository of Université Libre de Bruxelles (6)
- Digital Commons at Florida International University (1)
- Diposit Digital de la UB - Universidade de Barcelona (1)
- Duke University (10)
- eResearch Archive - Queensland Department of Agriculture; Fisheries and Forestry (6)
- FAUBA DIGITAL: Repositorio institucional científico y académico de la Facultad de Agronomia de la Universidad de Buenos Aires (2)
- Greenwich Academic Literature Archive - UK (13)
- Helda - Digital Repository of University of Helsinki (22)
- Indian Institute of Science - Bangalore - Índia (136)
- Instituto Politécnico do Porto, Portugal (1)
- Massachusetts Institute of Technology (4)
- Ministerio de Cultura, Spain (4)
- National Center for Biotechnology Information - NCBI (1)
- Nottingham eTheses (2)
- Plymouth Marine Science Electronic Archive (PlyMSEA) (14)
- Publishing Network for Geoscientific & Environmental Data (2)
- QUB Research Portal - Research Directory and Institutional Repository for Queen's University Belfast (154)
- Queensland University of Technology - ePrints Archive (142)
- ReCiL - Repositório Científico Lusófona - Grupo Lusófona, Portugal (1)
- Repositório Institucional da Universidade de Aveiro - Portugal (1)
- Repositorio Institucional de la Universidad Pública de Navarra - Espanha (1)
- Repositório Institucional dos Hospitais da Universidade Coimbra (1)
- Repositório Institucional UNESP - Universidade Estadual Paulista "Julio de Mesquita Filho" (1)
- RUN (Repositório da Universidade Nova de Lisboa) - FCT (Faculdade de Cienecias e Technologia), Universidade Nova de Lisboa (UNL), Portugal (2)
- SAPIENTIA - Universidade do Algarve - Portugal (1)
- School of Medicine, Washington University, United States (5)
- Universidad de Alicante (1)
- Universidad del Rosario, Colombia (1)
- Universidad Politécnica de Madrid (4)
- Universidade de Lisboa - Repositório Aberto (2)
- Universidade Federal do Pará (1)
- Universitat de Girona, Spain (1)
- Universitätsbibliothek Kassel, Universität Kassel, Germany (3)
- Université de Lausanne, Switzerland (15)
- Université de Montréal, Canada (12)
- University of Queensland eSpace - Australia (3)
- University of Southampton, United Kingdom (2)
- University of Washington (2)
Relevância:
Resumo:
The statistical analysis of compositional data is commonly used in geological studies. As is well-known, compositions should be treated using logratios of parts, which are difficult to use correctly in standard statistical packages. In this paper we describe the new features of our freeware package, named CoDaPack, which implements most of the basic statistical methods suitable for compositional data. An example using real data is presented to illustrate the use of the package