predict-D2C-method: predict if there is a connection between node i and node j
In D2C: Predicting Causal Direction from Dependency Features

Description Usage Arguments Value References Examples

predict if there is a connection between node i and node j

1 2	## S4 method for signature 'D2C' predict(object, i, j, data)

`object`	: a D2C object
`i`	: index of putative cause (1 ≤ i ≤ n)
`j`	: index of putative effect (1 ≤ j ≤ n)
`data`	: dataset of observations from the DAG

list with response and prob of the prediction

Gianluca Bontempi, Maxime Flauder (2014) From dependency to causality: a machine learning approach. Under submission

require(RBGL)
require(gRbase)
require(foreach)
data(example)
## load the D2C object
testDAG<-new("simulatedDAG",NDAG=1, N=50,noNodes=5,
           functionType = "linear", seed=1,sdn=c(0.25,0.5))
## creates a simulatedDAG object for testing
plot(testDAG@list.DAGs[[1]])
## plot the topology of the simulatedDAG
predict(example,1,2, testDAG@list.observationsDAGs[[1]])
## predict if the edge 1->2 exists
predict(example,4,3, testDAG@list.observationsDAGs[[1]])
## predict if the edge 4->3 exists
predict(example,4,1, testDAG@list.observationsDAGs[[1]])
## predict if the edge 4->1 exists