tnam: Temporal Network Autocorrelation Models (TNAM)
Version 1.6.5

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) .

Package details

AuthorPhilip Leifeld [aut, cre], Skyler J. Cranmer [ctb]
Date of publication2017-04-01 06:30:55 UTC
MaintainerPhilip Leifeld <[email protected]>
LicenseGPL (>= 2)
Package repositoryView on CRAN
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tnam documentation built on May 29, 2017, 7:19 p.m.