print.HydeNetwork: Print a HydeNetwork

In HydeNet: Hybrid Bayesian Networks Using R and JAGS

Description

Prints a HydeNetwork object with a brief summary of each node.

Usage

## S3 method for class 'HydeNetwork'
print(x, ...)

Arguments

x	a HydeNetwork object
...	additional arguments to be passed to print methods. Currently none in use.

Details

The summary of each node follows the format
node name | parents
node type (parameter)
estimated from data (or not)
formula

Author(s)

Jarrod Dalton and Benjamin Nutter

Examples

data(PE, package="HydeNet")
Net <- HydeNetwork(~ wells + 
                     pe | wells + 
                     d.dimer | pregnant*pe + 
                     angio | pe + 
                     treat | d.dimer*angio + 
                     death | pe*treat) 
print(Net)  
print(Net, d.dimer) 
                    
Net <- setNode(Net, d.dimer, 
                  nodeType='dnorm', mean=fromData(), sd=fromData(), 
                  nodeFormula = d.dimer ~ pregnant + pe,
                  nodeFitter='lm')
print(Net, d.dimer)
    

Example output

Loading required package: nnet
A Probabilistic Graphical Network
Has data attached: No

wells
dnorm(mu = Unspecified, tau = Unspecified)
: wells ~ 1

pe | wells
dnorm(mu = Unspecified, tau = Unspecified)
: pe ~ wells

d.dimer | pe * pregnant
dnorm(mu = Unspecified, tau = Unspecified)
: d.dimer ~ pe + pregnant

pregnant
dnorm(mu = Unspecified, tau = Unspecified)
: pregnant ~ 1

angio | pe
dnorm(mu = Unspecified, tau = Unspecified)
: angio ~ pe

treat | d.dimer * angio
dnorm(mu = Unspecified, tau = Unspecified)
: treat ~ d.dimer + angio

death | pe * treat
dnorm(mu = Unspecified, tau = Unspecified)
: death ~ pe + treatA Probabilistic Graphical Network
Has data attached: No

d.dimer | pe * pregnant
dnorm(mu = Unspecified, tau = Unspecified)
: d.dimer ~ pe + pregnantA Probabilistic Graphical Network
Has data attached: No

d.dimer | pe * pregnant
dnorm(mean = fromData, sd = fromData)
lm: d.dimer ~ pregnant + pe

HydeNet documentation built on July 8, 2020, 5:15 p.m.