Discover the structure around a single node
Learn the Markov blanket or the neighbourhood centered on a node.
learn.mb(x, node, method, whitelist = NULL, blacklist = NULL, start = NULL, test = NULL, alpha = 0.05, B = NULL, max.sx = NULL, debug = FALSE) learn.nbr(x, node, method, whitelist = NULL, blacklist = NULL, test = NULL, alpha = 0.05, B = NULL, max.sx = NULL, debug = FALSE)
x |
a data frame containing the variables in the model. |
node |
a character string, the label of the node whose local structure is being learned. |
method |
a character string, the label of a structure learning algorithm. Possible choices are listed in structure learning. |
whitelist |
a vector of character strings, the labels of the whitelisted nodes. |
blacklist |
a vector of character strings, the labels of the blacklisted nodes. |
start |
a vector of character strings, the labels of the nodes to be
included in the Markov blanket before the learning process (in
|
test |
a character string, the label of the conditional independence test
to be used in the algorithm. If none is specified, the default test
statistic is the mutual information for categorical variables, the
Jonckheere-Terpstra test for ordered factors and the linear
correlation for continuous variables. See |
alpha |
a numeric value, the target nominal type I error rate. |
B |
a positive integer, the number of permutations considered for each
permutation test. It will be ignored with a warning if the conditional
independence test specified by the |
max.sx |
a positive integer, the maximum allowed size of the conditioning sets used in conditional independence tests. The default is that there is no limit on size. |
debug |
a boolean value. If |
A vector of character strings, the labels of the nodes in the Markov blanket
(for learn.mb()) or in the neighbourhood (for learn.nbr()).
Marco Scutari
learn.mb(learning.test, node = "D", method = "iamb")
learn.mb(learning.test, node = "D", method = "iamb", blacklist = c("A", "F"))
learn.nbr(gaussian.test, node = "F", method = "si.hiton.pc", whitelist = "D")Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.