Cargando…
Robust rankings: Review of multivariate assessments illustrated by the Shanghai rankings
Defined errors are entered into data collections in order to test their influence on the reliability of multivariate rankings. Random numbers and real ranking data serve as data origins. In the course of data collection small random errors often lead to a switch in ranking, which can influence the g...
Autor principal: | Freyer, Leo |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2014
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4090748/ https://www.ncbi.nlm.nih.gov/pubmed/25018571 http://dx.doi.org/10.1007/s11192-014-1313-8 |
Ejemplares similares
-
Global Standing of Pak Universities in Shanghai Ranking
por: Meo, Sultan Ayoub
Publicado: (2018) -
Robust reduced-rank regression
por: She, Y., et al.
Publicado: (2017) -
Multivariate Assessment and Risk Ranking of Pesticide Residues in Citrus Fruits
por: Radulović, Jelena, et al.
Publicado: (2023) -
Multivariate reduced-rank regression: theory and applications
por: Reinsel, Gregory C, et al.
Publicado: (1998) -
Ranking of multivariate populations: a permutation approach with applications
por: Corain, Livio, et al.
Publicado: (2016)