pmlCluster {phangorn} | R Documentation |
Stochastic Partitioning of genes into p cluster.
pmlCluster(formula, fit, weight, p = 4, part = NULL, ...)
formula |
a formula object (see details). |
fit |
an object of class pml . |
weight |
weight is matrix of frequency of site patterns for all genes. |
p |
number of clusters. |
part |
starting partition, otherwise a random partiton is generated. |
... |
Further arguments passed to or from other methods. |
The formula
object allows to specify which parameter get
optimised. The formula is generally of the form edge + bf + Q
~ rate + shape + ...
, on the left side are the parameters which
get optimised over all cluster, on the right the parameter which
are optimised specific to each cluster. The parameters available
are "nni", "bf", "Q", "inv", "shape", "edge", "rate"
.
Each parameters can be used only once in the formula.
"rate"
is only available for the right side and so is
"nni"
.
pmlCluster
returns a list with elements
logLik |
log-likelihood of the fit |
trees |
a list of all trees during the optimisation. |
fits |
fits for the final partitions |
Klaus Schliep K.P.Schliep@massey.ac.nz
## Not run: data(yeast) dm <- dist.logDet(yeast) tree <- NJ(dm) fit=pml(tree,yeast) fit = optim.pml(fit) weight=xtabs(~ index+genes,attr(yeast, "index")) set.seed(1) sp <- pmlCluster(edge~rate, fit, weight, p=4) sp ## End(Not run)