Usage
mlogl(parm, pred, fam, x, root, modmat, deriv = 0,
type = c("unconditional", "conditional"), famlist = fam.default(),
origin, origin.type = c("model.type", "unconditional", "conditional"))Arguments
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(
fam
an integer vector of length nnode determining
the exponential family structure of the aster model. Each element
is an index into the vector of family specifications given by
the argument famlist.
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 mus
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 pred[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
deriv
derivative wanted: 0, 1, or 2.
type
type of model. The value of this argument can be abbreviated.
famlist
a list of family specifications (see families). origin
Distinguished point in parameter space. May be missing,
in which case an unspecified default is provided. See aster
for further explanation. origin.type
Parameter space in which specified distinguished point
is located. If "conditional" then argument "origin" is
a conditional canonical parameter value.
If "unconditional" then argument "origin"