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20152026
most citedOn a minimum distance procedure for threshold selection in tail analysis

23 citations · 49 across the 36 of their papers we have counts for

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6 papers · 1 filter

math.PR2024★ 1 cited

Emergence of Multivariate Extremes in Multilayer Inhomogeneous Random Graphs

Daniel Cirkovic, Tiandong Wang, Daren B. H. Cline

In this paper, we propose a multilayer inhomogeneous random graph model (MIRG), whose layers may consist of both single-edge and multi-edge graphs. In the single layer case, it has…

math.PR2020★ 1 cited

A Directed Preferential Attachment Model with Poisson Measurement

Tiandong Wang, Sidney I. Resnick

When modeling a directed social network, one choice is to use the traditional preferential attachment model, which generates power-law tail distributions. In a traditional directed…

math.PR2018★ 1 cited

Degree Growth Rates and Index Estimation in a Directed Preferential Attachment Model

Tiandong Wang, Sidney I. Resnick

Preferential attachment is widely used to model power-law behavior of degree distributions in both directed and undirected networks. In a directed preferential attachment model, de…

math.PR2017

Consistency of Hill Estimators in a Linear Preferential Attachment Model

Tiandong Wang, Sidney Resnick

Preferential attachment is widely used to model power-law behavior of degree distributions in both directed and undirected networks. Practical analyses on the tail exponent of the…

math.PR2016★ 3 cited

Multivariate Regular Variation of Discrete Mass Functions with Applications to Preferential Attachment Networks

Tiandong Wang, Sidney I. Resnick

Regular variation of a multivariate measure with a Lebesgue density implies the regular variation of its density provided the density satisfies some regularity conditions. Unlike t…

math.PR2015

Asymptotic Normality of In- and Out-Degree Counts in a Preferential Attachment Model

Tiandong Wang, Sidney I. Resnick

Preferential attachment in a directed scale-free graph is widely used to model the evolution of social networks. Statistical analyses of social networks often relies on node based…