multiloglikechain: Derive log-likelihood of conditional log-linear model given...

In youjin1207/netchain: Inferring Causal Effects on Collective Outcomes under Interference

Description

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

Usage

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

Arguments

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.

Value

log-likelihood of conditional log-linear model given parameters, observations, and edge information.

youjin1207/netchain documentation built on May 7, 2019, 9:32 a.m.