Minus the Log Likelihood for an Aster model, and its first and second
derivative. This function is called inside aster.
Users should not need to call it themselves unless they are doing
something the package is not designed to do.
parm |
parameter value (vector of regression coefficients)
where we evaluate the log likelihood, etc.
We also refer to length(parm) as ncoef. |
pred |
integer vector determining the graph.
pred[j] is the index of the predecessor of
the node with index j unless the predecessor is a root
node, in which case pred[j] == 0.
We also refer to length(pred) as nnode. |
fam |
integer vector of length nnode determining
the one-parameter exponential family associated with each node
of the graph. An index into the vector of family names returned by
families. |
x |
the response. If a matrix, rows are individuals, and columns are
variables (nodes of graphical model). So ncol(x) == nnode and
we also refer to nrow(x) as nind. If not a matrix, then
x must be as if it were such a matrix and then dimension
information removed by x = as.numeric(x). |
root |
A matrix or vector like x.
Data root[i, j] is the data for the founder that is
the predecessor of the response x[i, j]
and is ignored when p(j) > 0. |
modmat |
a three-dimensional array, nind by nnode by
ncoef, the model matrix. Or a matrix, nind * nnode by
ncoef (when x and root are one-dimensional
of length nind * nnode). |
deriv |
derivative wanted: 0, 1, or 2. |
type |
type of model. The value of this argument can be abbreviated. |