Temporal Network Autocorrelation Models (TNAM)

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) ; Hays, Kachi and Franzese (2010) ; Leenders, Roger Th. A. J. (2002) .


Reference manual

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1.6.5 by Philip Leifeld, 2 years ago


Browse source code at https://github.com/cran/tnam

Authors: Philip Leifeld [aut, cre] , Skyler J. Cranmer [ctb]

Documentation:   PDF Manual  

GPL (>= 2) license

Imports methods, utils, stats, network, sna, igraph, vegan, lme4, Rcpp

Depends on xergm.common

Suggests texreg

Linking to Rcpp

Depended on by xergm.

See at CRAN