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Search · four archives
22 papers · ranked by Valyu relevance
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- Graph and network: the terms are used interchangeably in this essay. - Real-world network: (real network, observed network) means network data the researcher has collected and is interested in modelling. - Ensemble of graphs: means the set of all possible graphs (network realizations) that the (real-world) network…
Alex Stivala, Alessandro Lomi
Analysis of the structure of biological networks often uses statistical tests to establish the over-representation of motifs, which are thought to be important building blocks of such networks, related to their biological functions. However, there is disagreement as to the statistical significance of these motifs, and…
Denise Helena Silva Duarte, Rafael Honório Pereira Alves
A class of models that have been widely used are the exponential random graph (ERG) models, which form a comprehensive family of models that include independent and dyadic edge models, Markov random graphs, and many other graph distributions, in addition to allow the inclusion of covariates that can lead to a better…
Masami Yoshida
In pedagogical practice, gratitude is recognised not as an emotion, but as an approach to learning. This study introduced gratitude messages into the academic online communication of university students and specifically examined the community in which students shared their messages with gratitude. This study examined…
Sa Ren, Xue Wang, Peng Liu, Jian Zhang
Ensembles of networks arise in various fields where multiple independent networks are observed on the same set of nodes, for example, a collection of brain networks constructed on the same brain regions for different individuals. However, there are few models that describe both the variations and characteristics of…
Johann Mourier, Marc Soria, Matthew Silk, Angélique Demichelis + 2 more
Animal movements are typically influenced by multiple environmental factors simultaneously and individuals vary in their response to this environmental heterogeneity. Therefore, understanding how environmental aspects, including biotic, abiotic and anthropogenic factors, influence the movements of wild animals is an…
Qiuchang (Katy) Cao, Holly Dabelko-Schoeny, Keith Warren, Mo Yee Lee
Few studies examined the social network structures within multicultural volunteer programs for low-income diverse older adults, making it unclear how diverse older adults establish social connections beyond their co-ethnic community. This study aims to identify the social network structures within a Senior Companion…
Brieuc Lehmann, Simon White
The collection of data on populations of networks is becoming increasingly common, where each data point can be seen as a realisation of a network-valued random variable. Moreover, each data point may be accompanied by some additional covariate information and one may be interested in assessing the effect of these…
Helal El-Zaatari, Fei Yu, Michael R. Kosorok, Pablo Martin Rodriguez
This study introduces a novel methodology for endogenous variable selection in Exponential Random Graph Models (ERGMs) to enhance the analysis of social networks across various scientific disciplines. Addressing critical challenges such as ERGM degeneracy and computational complexity, our method integrates a systematic…
Kayvan Sadeghi
We show that the only exponential random graph model with n nodal parameters, dyads being independent, and the natural assumption of permutation-equivariant nodal parametrization is the β model. In addition, we show that an exponential random graph model with similar assumptions but with fewer than n block parameters…
Helal El-Zaatari, F. Richard Yu, Michael R. Kosorok
Statistical analysis of social networks provides valuable insights into complex network interactions across various scientific disciplines. However, accurate modeling of networks remains challenging due to the heavy computational burden and the need to account for observed network dependencies. Exponential Random Graph…
Fan Yin, Carter T. Butts, Fabrizio De Vico Fallani
The exponential family random graph modeling (ERGM) framework provides a highly flexible approach for the statistical analysis of networks (i.e., graphs). As ERGMs with dyadic dependence involve normalizing factors that are extremely costly to compute, practical strategies for ERGMs inference generally employ a variety…
Adrian Fischer, Gesine Reinert, Wenkai Xu
Providing theoretical guarantees for parameter estimation in exponential random graph models is a largely open problem. While maximum likelihood estimation has theoretical guarantees in principle, verifying the assumptions for these guarantees to hold can be very difficult. Moreover, in complex networks, numerical…
Adam B. Rohrlach, Guido Alberto Gnecchi-Ruscone, Zuzana Hofmanová, Matthew Roughan + 2 more
Genetic relatedness between ancient humans can help to identify close and distant connections between groups and populations, uncovering signatures of demographic histories such as identifying mating networks or long-range migration. Critical to researchers are the characteristics that connected individuals, or groups…
Bram Mornie, Didier Colle, Pieter Audenaert, Mario Pickavet + 1 more
'Enrique Hernandez-Lemus'] Testing or benchmarking network algorithms in bioinformatics requires a diverse set of networks with realistic properties. Real networks are often supplemented by randomly generated synthetic ones, but most graph generative models do not take into account the distribution of subgraph…
Ruoyao Zhang, Gaurav Mitra, Souradeep Ghosh, Rohit V. Pappu
Multivalent biomacromolecules including multi-domain and intrinsically disordered proteins form biomolecular condensates via reversible phase transitions. Condensates are viscoelastic materials that display composition-specific rheological properties and responses to mechanical forces. Graph-based descriptions of…
Raima Carol Appaw, Matthew J Silk, Julie Rushmore, Kimberly VanderWaal + 2 more
Detecting patterns in animal social behaviour and movement is complicated by the diversity of ecological, evolutionary, environmental, and biological drivers of these behaviours such as migration, foraging, assortative mixing, socio-ecological factors, and human influence. Addressing these complexities requires a…
Nicholas Christiansen, Ioanna Sandvig, Axel Sandvig
Biological neural networks are characterized by short average path lengths, high clustering, and modular and hierarchical architectures. These complex network topologies strike a balance between local specialization and global synchronization via long-range connections, resulting in highly efficient communication.…
Fernando Alcalde Cuesta, Gustavo Guerberoff, Álvaro Lozano Rojo
In this paper, we study the absorption and fixation times for evolutionary processes on graphs, under different updating rules. While in Moran process a single neighbour is randomly chosen to be replaced, in proliferation processes other neighbours can be replaced using Bernoulli or binomial draws depending on 0 < p ≤…
Heather M. Shappell, Mark A. Kramer, Catherine J. Chu, Eric D. Kolaczyk
Stochastic Actor-Oriented Models (SAOMs) were designed in the social network setting to capture network dynamics representing a variety of influences on network change. The standard framework assumes the observed networks are free of false positive and false negative edges, which may be an unrealistic assumption. We…
Laura Eslava, Sayle Sigarreta Ricardo, Arno Siri-Jégousse
We prove that the generalized Randić index over graphs following the Erdos-Rényi model, for both the sparse and dense regimes, is concentrated around its mean when the number of vertices tends to infinity.
harry gray
The matrix exponential method as implemented in MATLAB is demonstrated as a facile tool for solving the time-dependent concentrations of an arbitrary chemically reactive network modelled as a coupled linear system of first-order differential equations. The method is used to verify a 10 species network incorporating…