Hyde-package: Hydbrid Decision Networks
In HydeNet: Hybrid Bayesian Networks Using R and JAGS
Description
Facilities for easy implementation of hybrid Bayesian networks
using R. Bayesian networks are directed acyclic graphs representing joint
probability distributions, where each node represents a random variable and
each edge represents conditionality. The full joint distribution is
therefore factorized as a product of conditional densities, where each node
is assumed to be independent of its non-descendants given information on its
parent nodes. Since exact, closed-form algorithms are computationally
burdensome for inference within hybrid networks that contain a combination
of continuous and discrete nodes, particle-based approximation techniques
like Markov Chain Monte Carlo are popular. We provide a user-friendly
interface to constructing these networks and running inference using rjags.
Econometric analyses (maximum expected utility under competing policies,
value of information) involving decision and utility nodes are also
supported.
HydeNet documentation built on July 8, 2020, 5:15 p.m.
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Description
Facilities for easy implementation of hybrid Bayesian networks using R. Bayesian networks are directed acyclic graphs representing joint probability distributions, where each node represents a random variable and each edge represents conditionality. The full joint distribution is therefore factorized as a product of conditional densities, where each node is assumed to be independent of its non-descendants given information on its parent nodes. Since exact, closed-form algorithms are computationally burdensome for inference within hybrid networks that contain a combination of continuous and discrete nodes, particle-based approximation techniques like Markov Chain Monte Carlo are popular. We provide a user-friendly interface to constructing these networks and running inference using rjags. Econometric analyses (maximum expected utility under competing policies, value of information) involving decision and utility nodes are also supported.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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