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Calculates -2*log-likelihood, AIC, and BIC for a triangulated graph (decomposable model).
fit(model=NULL, edges=NULL, dataset, homog=NULL)
gRapHD
object.
matrix with 2 columns, each row representing one edge, and each column one of the vertices in the edge.
matrix or data frame (nrow(dataset)
observations and
ncol(dataset)
variables).
only used in the mixed model case. TRUE
if the model is
homogeneous. The default is NULL
, indicating that the
attribute homog
of the model
parameter must be
used (or TRUE
if only edges
is provided).
Vector with: model dimension (no of free parameters), -2*log-likelihood, AIC, and BIC. Note that all parameters are assumed to be estimable in the dimension calculation.
Lauritzen, S.L. (1996) Graphical Models, Oxford University Press.
# NOT RUN {
data(dsCont)
m1 <- minForest(dsCont,homog=TRUE,forbEdges=NULL,stat="LR")
fit(edges=m1@edges,dataset=dsCont)
# }
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