posterior_pairwise: Posterior distribution over two graphs given prior and an...
In neilbramley/acl_source: Functions for active causal learning

Posterior distribution over two graphs given prior and an unfolding

1 2	posterior_pairwise(graph1, graph2, unfolding, prior = c(0.5, 0.5), pow = 0.75, sar = 0)

`graph1`	The first hypothesis
`graph2`	The second hypothesis
`unfolding`	the data
`prior`	the prior distribution (as a vector), defaults to c(.5,.5)
`pow`	strength of causal links, defaults to .75
`sar`	strengh of background causes, defaults to 0

1 2	out<-posterior_pairwise(matrix(c(1,1,0,0),2,2,byrow=T), matrix(c(1,0,0,0),2,2,byrow=T), generate_unfolding(matrix(c(1,1,0,0),2,2,byrow=T), c(1,0)))