tnam (1.6.5)

0 users

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) .

Maintainer: Philip Leifeld
Author(s): Philip Leifeld [aut, cre], Skyler J. Cranmer [ctb]

License: GPL (>= 2)

Uses: igraph, lme4, network, Rcpp, sna, vegan, xergm.common, texreg
Reverse depends: xergm

Released about 3 years ago.

3 previous versions



  (0 votes)


  (0 votes)

Log in to vote.


No one has written a review of tnam yet. Want to be the first? Write one now.

Related packages:(20 best matches, based on common tags.)

Search for tnam on google, google scholar, r-help, r-devel.

Visit tnam on R Graphical Manual.