Search · four archives
Search · four archives
15 papers · ranked by Valyu relevance
Yefeng Fan, Simon Richard White
Exponential random graph models (ERGMs) are flexible probabilistic frameworks to model statistical networks through a variety of network summary statistics. Conventional Bayesian estimation for ERGMs involves iteratively exchanging with an auxiliary variable due to the intractability of the ERGM likelihood. However…
Yuanyuan Shang, Philip Leifeld
In private capital investment, limited partners (LPs) and general partners (GPs) frequently encounter the challenge of finding suitable counterparts amid limited information, a process often hindered by market inefficiencies. This article addresses this issue by exploring the micro-level mechanisms that shape private…
Alfonso Landeros, Dhwani Krishnan, Kenneth Lange, Mary Sehl
Background Many networks contain node and edge data in the form of node-specific covariates and edge weights, respectively. Established methods for investigating graph structure often rely on dichotimizing edge data. This simplification motivates the development of techniques for multivariate analysis. In the context…
Armand M. Makowski, Siddharth Pal, Geert Verdoolaege
We discuss several limiting degree distributions for a class of homogeneous random graphs, known as random threshold graphs, in the many node regime. This analysis is carried out under a weak assumption on the distribution of the underlying fitness variable. This assumption, which is satisfied by the exponential…
Pawat Akara-pipattana, Oleg Evnin, Antonio M. Scarfone
The two-star random graph is the simplest exponential random graph model with nontrivial interactions between the graph edges. We propose a set of auxiliary variables that control the thermodynamic limit where the number of vertices N tends to infinity. Such ’master variables’ are usually highly desirable in treatments…
A. Y. Klimenko, A. Rozycki, Y. Lu, Zhigang Zheng
We explore a rigorous formulation of agent-based SIR epidemic dynamics as a discrete-state Markov process, capturing the stochastic propagation of infection or an invading agent on networks. Using indicator functions and corresponding marginal probabilities, we derive a hierarchy of evolution equations that resembles…
Changbo Zhu, Ke Zhou, Fengzhen Tang, Yandong Tang + 2 more
Brain activities often follow an exponential family of distributions. The exponential distribution is the maximum entropy distribution of continuous random variables in the presence of a mean. The memoryless and peakless properties of an exponential distribution impose difficulties for data analysis methods. To…
Xiaofang Luo, Haibo Hu, Qingsong Sun, Zi-Ke Zhang + 3 more
Information propagation in social media has attracted the wide attention of scholars, with great progress made in empirical and modeling studies. Branching processes, extensively utilized in theoretical biology, are increasingly applied to model information diffusion dynamics. However, detailed and data-driven studies…
Roxana Irina Iancu, Călin Gheorghe Buzea, Florin Nedeff, Diana Mirilă + 9 more
Complex diseases often involve distributed interactions among biological regions, physiological systems, imaging phenotypes, and clinical variables that are not fully captured by anatomical proximity, isolated biomarkers, or conventional feature-based representations. In oncology, neuroimaging, critical care, and…
Luiz Desuó Neto, Henrique de Oliveira Caetano, Matheus de Souza Sant’Anna Fogliatto, Carlos Dias Maciel + 1 more
Learning dependence graphs from multivariate continuous data is challenging when marginal distributions are heterogeneous, since likelihood-based nonparametric scores can be sensitive to smoothing choices and can confound marginal irregularities, including non-identifiability, with dependence. This work studies…
M. N. Mooij, M. Baudena, A. S. von der Heydt, L. Miele + 1 more
Triangles are abundant in real-world networks but rare in standard null models for sparse graphs. Existing explanations typically rely on explicit triadic closure mechanisms or geometry-based connection rules. We propose an alternative hypothesis: the frequent appearance of triangles may arise naturally from the…
Seth Sullivant
The displayed tree phylogenetic network model is shown to sit as a natural submodel of the graphical model associated to a directed acyclic graph (DAG). This representation allows us to derive a number of results about the displayed tree model. In particular, the concept of a local modification to a DAG model is…
Chay Paterson, Miaomiao Gao, Joshua Hellier, Georg Luebeck + 3 more
Compound birth-death processes are widely used to model the age-incidence curves of many cancers. There are efficient schemes for directly computing the relevant probability distributions in the context of linear multi-stage clonal expansion (MSCE) models. However, these schemes have not been generalised to models on…
Mariah C. Boudreau, William H. W. Thompson, Christopher M. Danforth, Jean-Gabriel Young + 1 more
Epidemic forecasting tools embrace the stochasticity and heterogeneity of disease spread to predict the growth and size of outbreaks. Conceptually, stochasticity and heterogeneity are often modelled as branching processes or as percolation on contact networks. Mathematically, probability generating functions (PGFs)…
William Casey, Leigh Metcalf, Shirshendu Chatterjee, Heeralal Janwa + 3 more
Many real-world problems feature nonlinear dynamic processes. Classical mathematical models may be adequate to describe a single dynamic process in isolation, but can be easily undermined by two natural and simple kinds of phenomenological variations: the emergence (or activation) of an additional dynamic process, and…