Cargando…
Bootstrap quantification of estimation uncertainties in network degree distributions
We propose a new method of nonparametric bootstrap to quantify estimation uncertainties in functions of network degree distribution in large ultra sparse networks. Both network degree distribution and network order are assumed to be unknown. The key idea is based on adaptation of the “blocking” argu...
Autores principales: | Gel, Yulia R., Lyubchich, Vyacheslav, Ramirez Ramirez, L. Leticia |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2017
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5517433/ https://www.ncbi.nlm.nih.gov/pubmed/28724937 http://dx.doi.org/10.1038/s41598-017-05885-x |
Ejemplares similares
-
Evaluating statistical uncertainties and correlations using the bootstrap method
por: The ATLAS collaboration
Publicado: (2021) -
Bootstrap-after-Bootstrap Model Averaging for Reducing Model Uncertainty in Model Selection for Air Pollution Mortality Studies
por: Roberts, Steven, et al.
Publicado: (2010) -
Bootstrap Resampling of Temporal Dominance of Sensations Curves to Compute Uncertainties
por: Okamoto, Shogo
Publicado: (2021) -
Using the Wild Bootstrap to Quantify Uncertainty in Mean Apparent Propagator MRI
por: Gu, Xuan, et al.
Publicado: (2019) -
Incorporating alignment uncertainty into Felsenstein’s phylogenetic bootstrap to improve its reliability
por: Chang, Jia-Ming, et al.
Publicado: (2019)