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BF {bnlearn} | R Documentation |
Bayes factor between two network structures
Description
Compute the Bayes factor between the structures of two Bayesian networks..
Usage
BF(num, den, data, score, ..., log = TRUE)
Arguments
num , den |
two objects of class |
data |
a data frame containing the data to be used to compute the Bayes factor. |
score |
a character string, the label of a posterior network score or |
... |
extra tuning arguments for the posterior scores. See |
log |
a boolean value. If |
Value
A single numeric value, the Bayes factor of the two network structures num
and
den
.
Note
The Bayes factor for two network structures, by definition, is the ratio of the respective marginal
likelihoods which is equivalent to the ration of the corresponding posterior probabilities if we assume the
uniform
prior over all possible DAGs. However, note that it is possible to specify different
priors using the “...
” arguments of BF()
; in that case the value
returned by the function will not be the classic Bayes factor.
Author(s)
Marco Scutari
See Also
Examples
data(learning.test)
dag1 = model2network("[A][B][F][C|B][E|B][D|A:B:C]")
dag2 = model2network("[A][C][B|A][D|A][E|D][F|A:C:E]")
BF(dag1, dag2, learning.test, score = "bds", iss = 1)
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