[HTML][HTML] Connectivity, coverage and placement in wireless sensor networks

J Li, LLH Andrew, CH Foh, M Zukerman, HH Chen - Sensors, 2009‏ - mdpi.com
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 …

Social network modeling

V Amati, A Lomi, A Mira - Annual Review of Statistics and Its …, 2018‏ - annualreviews.org
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 …

Inferential network analysis with exponential random graph models

SJ Cranmer, BA Desmarais - Political analysis, 2011‏ - cambridge.org
Methods for descriptive network analysis have reached statistical maturity and general
acceptance across the social sciences in recent years. However, methods for statistical …

Modeling knowledge networks in economic geography: a discussion of four methods

T Broekel, PA Balland, M Burger, F van Oort - The annals of regional …, 2014‏ - Springer
The importance of network structures for the transmission of knowledge and the diffusion of
technological change has been recently emphasized in economic geography. Since …

Network dynamics and the evolution of international cooperation

BJ Kinne - American Political Science Review, 2013‏ - cambridge.org
Cooperation helps states realize mutual gains, but mistrust and disagreements over
institutional design inhibit cooperation. This article develops a network explanation for how …

Statistical mechanics of networks: Estimation and uncertainty

BA Desmarais, SJ Cranmer - Physica A: statistical mechanics and its …, 2012‏ - Elsevier
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 …

A framework for the comparison of maximum pseudo-likelihood and maximum likelihood estimation of exponential family random graph models

MAJ Van Duijn, KJ Gile, MS Handcock - Social networks, 2009‏ - Elsevier
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 …

Exponential random graph modeling for complex brain networks

SL Simpson, S Hayasaka, PJ Laurienti - PloS one, 2011‏ - journals.plos.org
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 …

The evolution and formation of amicus curiae networks

JM Box-Steffensmeier, DP Christenson - Social Networks, 2014‏ - Elsevier
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 …

Explaining the structure of inter-organizational networks using exponential random graph models

T Broekel, M Hartog - Industry and innovation, 2013‏ - Taylor & Francis
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 …