multiloglikechain: Derive log-likelihood of conditional log-linear model given...
In netchain: Inferring Causal Effects on Collective Outcomes under Interference

Derive log-likelihood of conditional log-linear model given parameters.

1	multiloglikechain(pars, listobservations, permutetab, edgeY, edgeAY, edgeExtra)

`pars`	a set of parameters
`listobservations`	a collection of `[(2+nc) x m ]` matrices comprised of outcomes (first row), treatments (second row), and confounders (from the third row), where `nc` is the number of confounders.
`permutetab`	a matrix comprised of every possible values for outcome in each row.
`edgeY`	a matrix of which each row indicates a pair of index for adjacent outcomes.
`edgeAY`	a matrix of which each row indicates a index for treatment (first column) and for outcome (second column) on which the treatment has a direct effect.
`edgeExtra`	a list of edges of which a list of matrix specifying additional directed edges (from confounders or treatment to the outcomes) information.