This is a paper as part of the reviewed proceedings of the ICML 2006 Workshop on Statistical Network Analysis, entitled 'Statistical Network Analysis: Models, Issues, and New Directions' published in the Lecture Notes in Computer Science Series. …
This is a discussion of the ICML 2006 Workshop on Statistical Network Analysis, entitled 'Statistical Network Analysis: Models, Issues, and New Directions' published in the Lecture Notes in Computer Science Series.
Objective: We present a likelihood based statistical framework to test the fit of power-law and alternative social process models for the degree distribution, and derive the sexually transmitted infection epidemic predictions from each model. Study …
Most inference using social network models assumes that the presence or absence of all relations is known. This is rarely the case. Most social network analysis ignores the problem of missing data by including only actors with complete observations. …
Network data arise in a wide variety of applications. Although descriptive statistics for networks abound in the literature, the science of fitting statistical models to complex network data is still in its infancy. The models considered in this …
Epidemic thresholds in network models of heterogeneous populations characterized by highly right-skewed contact distributions can be very small. When the population is above the threshold, an epidemic is inevitable and conventional control measures …
Recent advances in latent space and related random effects models hold much promise for representing network data. The inherent dependency between ties in a network makes modeling data of this type difficult. In this article we consider a recently …
The most promising class of statistical models for expressing structural properties of social networks observed at one moment in time is the class of exponential random graph models (ERGMs), also known as p* models. The strong point of these models …
Network models are widely used to represent relations among interacting units or actors. Network data often exhibit transitivity, meaning that two actors that have ties to a third actor are more likely to be tied than actors that do not, homophily by …
Network data arise in a wide variety of applications. Although descriptive statistics for networks abound in the literature, the science of fitting statistical models to complex network data is still in its infancy. The models considered in this …