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[HTML][HTML] Connectivity, coverage and placement in wireless sensor networks
Wireless communication between sensors allows the formation of flexible sensor networks,
which can be deployed rapidly over wide or inaccessible areas. However, the need to …
which can be deployed rapidly over wide or inaccessible areas. However, the need to …
Social network modeling
The development of stochastic models for the analysis of social networks is an important
growth area in contemporary statistics. The last few decades have witnessed the rapid …
growth area in contemporary statistics. The last few decades have witnessed the rapid …
Inferential network analysis with exponential random graph models
Methods for descriptive network analysis have reached statistical maturity and general
acceptance across the social sciences in recent years. However, methods for statistical …
acceptance across the social sciences in recent years. However, methods for statistical …
Modeling knowledge networks in economic geography: a discussion of four methods
The importance of network structures for the transmission of knowledge and the diffusion of
technological change has been recently emphasized in economic geography. Since …
technological change has been recently emphasized in economic geography. Since …
Network dynamics and the evolution of international cooperation
Cooperation helps states realize mutual gains, but mistrust and disagreements over
institutional design inhibit cooperation. This article develops a network explanation for how …
institutional design inhibit cooperation. This article develops a network explanation for how …
Statistical mechanics of networks: Estimation and uncertainty
Exponential random graph models (ERGMs) are powerful tools for formulating theoretical
models of network generation or learning the properties of empirical networks. They can be …
models of network generation or learning the properties of empirical networks. They can be …
A framework for the comparison of maximum pseudo-likelihood and maximum likelihood estimation of exponential family random graph models
The statistical modeling of social network data is difficult due to the complex dependence
structure of the tie variables. Statistical exponential families of distributions provide a flexible …
structure of the tie variables. Statistical exponential families of distributions provide a flexible …
Exponential random graph modeling for complex brain networks
Exponential random graph models (ERGMs), also known as p* models, have been utilized
extensively in the social science literature to study complex networks and how their global …
extensively in the social science literature to study complex networks and how their global …
The evolution and formation of amicus curiae networks
This paper sheds light on two age-old questions of interest group behavior: how have
interest group coalition strategies changed over time and which factors determine whether …
interest group coalition strategies changed over time and which factors determine whether …
Explaining the structure of inter-organizational networks using exponential random graph models
A key question raised in recent years is what factors determine the structure of inter-
organizational networks. Most research so far has focused on different forms of proximity …
organizational networks. Most research so far has focused on different forms of proximity …