
Last chance! 50% off unlimited learning
Sale ends in
Build a model string from a Bayesian network and vice versa.
modelstring(x)
modelstring(x, debug = FALSE) <- valuemodel2network(string, ordering = NULL, debug = FALSE)
# S3 method for bn
as.character(x, ...)
# S3 method for character
as.bn(x, ...)
model2network()
and as.bn()
return an object of class bn
;
modelstring()
and as.character.bn()
return a character string.
an object of class bn
. modelstring()
(but not its
replacement form) accepts also objects of class bn.fit
.
a character string describing the Bayesian network.
the labels of all the nodes in the graph; their order is the
node ordering used in the construction of the bn
object. If
NULL
the nodes are sorted alphabetically.
a character string, the same as the string
.
a boolean value. If TRUE
a lot of debugging output is
printed; otherwise the function is completely silent.
extra arguments from the generic method (currently ignored).
Marco Scutari
The strings returned by modelstringi()
have the same format as the ones
returned by the modelstring()
function in package deal; network
structures may be easily exported to and imported from that package (via the
model2network
function).
The format of the model strings is as follows. The local structure of each
node is enclosed in square brackets ("[]
"); the first string is the
label of that node. The parents of the node (if any) are listed after a
("|
") and separated by colons (":
"). All nodes (including
isolated and root nodes) must be listed.
data(learning.test)
dag = hc(learning.test)
dag
modelstring(dag)
dag2 = model2network(modelstring(dag))
dag2
all.equal(dag, dag2)
Run the code above in your browser using DataLab