| boot.strength {bnlearn} |
R Documentation |
Bootstrap arc strength and direction
Description
Use nonparametric bootstrap to assess arc strength and direction.
Usage
boot.strength(data, R = 200, m = nrow(data),
algorithm, algorithm.args = list(), debug = FALSE)
Arguments
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. |
Value
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). |
Author(s)
Marco Scutari
References
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.
See Also
arc.strength, bn.boot.
