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HydeNet  

Hybrid Bayesian Networks Using R and JAGS
View on CRAN: Click here


Download and install HydeNet package within the R console
Install from CRAN:
install.packages("HydeNet")

Install from Github:
library("remotes")
install_github("cran/HydeNet")

Install by package version:
library("remotes")
install_version("HydeNet", "0.10.11")



Attach the package and use:
library("HydeNet")
Maintained by
Benjamin Nutter
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2015-07-03
Latest Update:
Description:
Facilities for easy implementation of hybrid Bayesian networksusing R. Bayesian networks are directed acyclic graphs representing jointprobability distributions where each node represents a random variable andeach edge represents conditionality. The full joint distribution is thereforefactorized as a product of conditional densities where each node is assumedto be independent of its non-descendents given information on its parent nodes.Since exact closed-form algorithms are computationally burdensome for inferencewithin hybrid networks that contain a combination of continuous and discretenodes particle-based approximation techniques like Markov Chain Monte Carloare popular. We provide a user-friendly interface to constructing these networksand running inference using the rjags package. Econometric analyses maximumexpected utility under competing policies value of information involvingdecision and utility nodes are also supported.
How to cite:
Benjamin Nutter (2015). HydeNet: Hybrid Bayesian Networks Using R and JAGS. R package version 0.10.11, https://cran.r-project.org/web/packages/HydeNet. Accessed 04 Jun. 2026.
Previous versions and publish date:
0.9.0 (2015-07-03 00:32), 0.10.0 (2015-10-12 00:47), 0.10.3 (2016-02-05 19:41), 0.10.4 (2016-07-08 19:51), 0.10.5 (2017-01-13 15:26), 0.10.6 (2017-12-01 18:18), 0.10.7 (2018-01-03 00:07), 0.10.8 (2018-07-19 19:10), 0.10.9 (2019-01-11 18:00), 0.10.10 (2020-05-15 15:40), 0.10.11 (2020-07-06 17:20)
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