boot.strength {bnlearn} | R Documentation |
Use nonparametric bootstrap to assess arc strength and direction.
boot.strength(data, R = 200, m = nrow(data), algorithm, algorithm.args = list(), debug = FALSE)
data |
a data frame, containing the variables in the model. |
R |
a positive integer, the number of bootstrap replicates. |
m |
a positive integer, the size of each bootstrap replicate. |
algorithm |
a character string, the learning algorithm to be
applied to the bootstrap replicates. Possible values are gs ,
iamb , fast.iamb , inter.iamb , mmpc
and hc . See bnlearn-package and the
documentation of each algorithm for details. |
algorithm.args |
a list of extra arguments to be passed to the learning algorithm. |
debug |
a boolean value. If TRUE a lot of debugging output
is printed; otherwise the function is completely silent. |
A 4-column data frame (very similar to an object of class
bn.strength
) with an entry for each possible arc in
the network and the following columns:
from, to |
the nodes incident on the arc. |
strength |
the strength of the arc, computed as the probability
of observing an arc between from and to in the bootstrap
replicates, regardless of its direction. |
direction |
the confidence in the direction of the arc, computed
as the probability of that particular direction in the bootstrap
replicates conditional on the presence of an arc between from
and to (again regardless of its direction). |
Marco Scutari
Imoto S, Kim SY, Shimodaira H, Aburatani S, Tashiro K, Kuhara S, Miyano S (2002). "Bootstrap Analysis of Gene Networks Based on Bayesian Networks and Nonparametric Regression". Genome Informatics, 13, 369-370.