Zobrazeno 1 - 10
of 274
pro vyhledávání: '"Wolfe, Patrick"'
Data structures known as $k$-d trees have numerous applications in scientific computing, particularly in areas of modern statistics and data science such as range search in decision trees, clustering, nearest neighbors search, local regression, and s
Externí odkaz:
http://arxiv.org/abs/2201.08288
Designing scalable estimation algorithms is a core challenge in modern statistics. Here we introduce a framework to address this challenge based on parallel approximants, which yields estimators with provable properties that operate on the entirety o
Externí odkaz:
http://arxiv.org/abs/2112.15572
We adopt the statistical framework on robustness proposed by Watson and Holmes in 2016 and then tackle the practical challenges that hinder its applicability to network models. The goal is to evaluate how the quality of an inference for a network fea
Externí odkaz:
http://arxiv.org/abs/2012.02914
We propose a general framework for modelling network data that is designed to describe aspects of non-exchangeable networks. Conditional on latent (unobserved) variables, the edges of the network are generated by their finite growth history (with lat
Externí odkaz:
http://arxiv.org/abs/2007.14365
This article introduces a new class of models for multiple networks. The core idea is to parametrize a distribution on labelled graphs in terms of a Fr\'{e}chet mean graph (which depends on a user-specified choice of metric or graph distance) and a p
Externí odkaz:
http://arxiv.org/abs/1904.07367
Some of the most used sampling mechanisms that implicitly leverage a social network depend on tuning parameters; for instance, Respondent-Driven Sampling (RDS) is specified by the number of seeds and maximum number of referrals. We are interested in
Externí odkaz:
http://arxiv.org/abs/1811.07829
The topology of any complex system is key to understanding its structure and function. Fundamentally, algebraic topology guarantees that any system represented by a network can be understood through its closed paths. The length of each path provides
Externí odkaz:
http://arxiv.org/abs/1705.05677
Autor:
Franke, Beate, Wolfe, Patrick J.
We characterize the large-sample properties of network modularity in the presence of covariates, under a natural and flexible nonparametric null model. This provides for the first time an objective measure of whether or not a particular value of modu
Externí odkaz:
http://arxiv.org/abs/1603.01214