Package: tnam
Version: 1.6.5
Date: 2017-03-31
Title: Temporal Network Autocorrelation Models (TNAM)
Authors@R: c(person(given = "Philip", family = "Leifeld", email = "philip.leifeld@glasgow.ac.uk", role = c("aut", "cre")), person(given = c("Skyler", "J."), family = "Cranmer", email = "cranmer.12@osu.edu", role = "ctb"))
Description: 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) <doi:10.1177/0049124184013002001>; Hays, Kachi and Franzese (2010) <doi:10.1016/j.stamet.2009.11.005>; Leenders, Roger Th. A. J. (2002) <doi:10.1016/S0378-8733(01)00049-1>.
URL: http://github.com/leifeld/tnam
Depends: R (>= 2.14.0), xergm.common (>= 1.7.7)
Imports: methods, utils, stats, network, sna, igraph, vegan, lme4 (>=
        1.0), Rcpp (>= 0.11.0)
Suggests: texreg
License: GPL (>= 2)
LinkingTo: Rcpp
NeedsCompilation: yes
Packaged: 2017-03-31 21:21:08 UTC; philip
Author: Philip Leifeld [aut, cre],
  Skyler J. Cranmer [ctb]
Maintainer: Philip Leifeld <philip.leifeld@glasgow.ac.uk>
Repository: CRAN
Date/Publication: 2017-04-01 06:30:55 UTC
