| Name : R-BANAM
| |
| Version : 0.2.1
| Vendor : obs://build_opensuse_org/devel:languages:R
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| Release : lp155.2.1
| Date : 2024-06-28 14:28:50
|
| Group : Development/Libraries/Other
| Source RPM : R-BANAM-0.2.1-lp155.2.1.src.rpm
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| Size : 0.62 MB
| |
| Packager : https://www_suse_com/
| |
| Summary : Bayesian Analysis of the Network Autocorrelation Model
|
Description :
The network autocorrelation model (NAM) can be used for studying the
degree of social influence regarding an outcome variable based on one
or more known networks. The degree of social influence is quantified
via the network autocorrelation parameters. In case of a single
network, the Bayesian methods of Dittrich, Leenders, and Mulder (2017)
< DOI:10.1016/j.socnet.2016.09.002> and Dittrich, Leenders, and Mulder
(2019) < DOI:10.1177/0049124117729712> are implemented using a normal,
flat, or independence Jeffreys prior for the network autocorrelation.
In the case of multiple networks, the Bayesian methods of Dittrich,
Leenders, and Mulder (2020) < DOI:10.1177/0081175020913899> are
implemented using a multivariate normal prior for the network
autocorrelation parameters. Flat priors are implemented for estimating
the coefficients. For Bayesian testing of equality and
order-constrained hypotheses, the default Bayes factor of Gu, Mulder,
and Hoijtink, (2018) < DOI:10.1111/bmsp.12110> is used with the
posterior mean and posterior covariance matrix of the NAM parameters
based on flat priors as input.
|
RPM found in directory: /packages/linux-pbone/ftp5.gwdg.de/pub/opensuse/repositories/devel:/languages:/R:/autoCRAN/15.5/x86_64 |
