bnlearn (version 2.0)

boot.strength: 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

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).

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, bnboot.