Provides methods for estimating parameter-dependent network centrality measures with linear-in-means models. Both non linear least squares and maximum likelihood estimators are implemented. The methods allow for both link and node heterogeneity in network effects, endogenous network formation and the presence of unconnected nodes. The routines also compare the explanatory power of parameter-dependent network centrality measures with those of standard measures of network centrality. Benefits and features of the 'econet' package are illustrated using data from Battaglini and Patacchini (2018) and Battaglini, Patacchini, and Leone Sciabolazza (2020). For additional details, see the vignette <doi:10.18637/jss.v102.i08>.
Package details |
|
---|---|
Author | Marco Battaglini [aut] (<https://orcid.org/0000-0001-9690-0721>), Valerio Leone Sciabolazza [aut, cre] (<https://orcid.org/0000-0003-2537-3084>), Eleonora Patacchini [aut] (<https://orcid.org/0000-0002-3510-2969>), Sida Peng [aut] (<https://orcid.org/0000-0002-2151-0523>) |
Maintainer | Valerio Leone Sciabolazza <valerio.leonesciabolazza@uniroma1.it> |
License | MIT + file LICENSE |
Version | 1.0.0.1 |
Package repository | View on CRAN |
Installation |
Install the latest version of this package by entering the following in R:
|
Any scripts or data that you put into this service are public.
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.