rewriteHydeFormula

The current formula in a <code>HydeNetwork</code> object.

old_form

The formula specifications to be added

new_form

This is a convenience function used to assist in the updating 
 of <code>HydeNetwork</code> network objects. It makes it possible to add and 
 subtract individual parent relationships without deleting an entire node.

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-descendents 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 the 'rjags' package. Econometric analyses (maximum
expected utility under competing policies, value of information) involving
decision and utility nodes are also supported.

rewriteHydeFormula: Rewrite HydeNetwork Graph Model Formula

Description

Usage

Arguments

Details