likelihoods-methods {Rtreemix} | R Documentation |
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.
## 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)