CRAN
tnam 1.6.5
Temporal Network Autocorrelation Models (TNAM)
Released Apr 1, 2017 by Philip Leifeld
Dependencies
xergm.common 1.7.7 sna 2.4 network 1.13.0.1 vegan 2.5-2 Rcpp lme4 1.1-18-1 igraph 1.2.2
Temporal and cross-sectional network autocorrelation models. These are models for variation in attributes of nodes nested in a network (e.g., drinking behavior of adolescents nested in a school class, or democracy versus autocracy of countries nested in the network of international relations). These models can be estimated for cross-sectional data or panel data, with complex network dependencies as predictors, multiple networks and covariates, arbitrary outcome distributions, and random effects or time trends. Basic references: Doreian, Teuter and Wang (1984)