Publication: Weighted dependency graphs
Weighted dependency graphs
Date
Date
Date
Citations
Féray, V. (2018). Weighted dependency graphs. Electronic Journal of Probability, 23(93), 1–65. https://doi.org/10.1214/18-ejp222
Abstract
Abstract
Abstract
The theory of dependency graphs is a powerful toolbox to prove asymptotic normality of sums of random variables. In this article, we introduce a more general notion of weighted dependency graphs and give normality criteria in this context. We also provide generic tools to prove that some weighted graph is a weighted dependency graph for a given family of random variables. To illustrate the power of the theory, we give applications to the following objects: uniform random pair partitions, the random graph model $G(n,M)$, uniform random
Metrics
Downloads
Views
Additional indexing
Creators (Authors)
Volume
Volume
Volume
Number
Number
Number
Page range/Item number
Page range/Item number
Page range/Item number
Page end
Page end
Page end
Item Type
Item Type
Item Type
In collections
Keywords
Language
Language
Language
Publication date
Publication date
Publication date
Date available
Date available
Date available
ISSN or e-ISSN
ISSN or e-ISSN
ISSN or e-ISSN
OA Status
OA Status
OA Status
Free Access at
Free Access at
Free Access at
Publisher DOI
Metrics
Downloads
Views
Citations
Féray, V. (2018). Weighted dependency graphs. Electronic Journal of Probability, 23(93), 1–65. https://doi.org/10.1214/18-ejp222