generate-methods {Rtreemix} | R Documentation |
Function for generating a random mutagenetic mixture model. Each tree component from the model is drawn uniformly at random from the tree topology space by using the Pr"ufer encoding of trees. The number of tree components and the number of genetic events have to be specified.
## S4 method for signature 'numeric, numeric': generate(K, no.events, ...)
K |
An integer larger than 0 specifying the number of
branchings in the mixture model. |
no.events |
An integer larger than 0 specifying the number of
genetic events in the mixture model. |
... |
noise.tree is a logical indicating the presence of a noise
(star) component in the random mixture model. The default value is
TRUE .
equal.edgeweights is a logical specifying whether to use
equal edge weights in the noise component. The default value is
TRUE .
prob is a numeric vector of length 2 specifying the
boundaries for the edge weights of the randomly generated trees. The
first component of the vector (the lower boundary) must be smaller
than the second component (the upper boundary). The default value
is (0.0, 1.0).
seed is a positive integer specifying the random generator
seed. The default value is (-1) and then the time is used as a
random generator.
|
The method returns an RtreemixModel
object that represents the
randomly generated K-trees mixture model.
Jasmina Bogojeska
Beweis eines Satzes "uber Permutationen, H. Pr"ufer; Learning multiple evolutionary pathways from cross-sectional data, N. Beerenwinkel et al.; Model Selection for Mixtures of Mutagenetic Trees, Yin et al.
## Generate a random RtreemixModel object with 3 components and 9 genetic events. rand.mod <- generate(K = 3, no.events = 9, noise.tree = TRUE, prob = c(0.2, 0.8)) show(rand.mod)