likelihoods-methods: Method for predicting the likelihoods of a set of samples...
In Rtreemix: Rtreemix: Mutagenetic trees mixture models.

Description Usage Arguments Value Author(s) References See Also Examples

This function predicts the (log, weighted) likelihoods of the samples in a given dataset according to a given mutagenetic trees mixture model. The dataset and the model have to be specified.

1 2	## S4 method for signature 'RtreemixModel,RtreemixData' likelihoods(model, data)

`model`	An `RtreemixModel` object specifying the probabilistic framework in which the likelihoods of the genetic patterns are computed.
`data`	An `RtreemixData` object giving the samples for which the likelihoods are to be calculated.

This method returns an RtreemixStats object that containes the weghted- and log-likelihoods of the samples in the given dataset with respect to the given mutagenetic trees mixture model.

Jasmina Bogojeska

Learning multiple evolutionary pathways from cross-sectional data, N. Beerenwinkel et al.

RtreemixData-class, RtreemixModel-class, fit-methods, distribution-methods

## Create an RtreemixData object from a randomly generated RtreemixModel object.
rand.mod <- generate(K = 3, no.events = 9, noise.tree = TRUE, prob = c(0.2, 0.8))
data <- sim(model = rand.mod, no.draws = 300)
show(data)

## Compute the likelihoods of the samples in data with respect to the model rand.mod
mod.stat <- likelihoods(model = rand.mod, data = data)
show(mod.stat)