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 parameter can be used only once in the formula.
There are also some restriction on the combinations how parameters
can get used. "rate"
is only available for the right side.
When "rate"
is speciefied on the left hand side "edge"
has to be specified (on either side), if "rate"
is specified on
the right hand side it follows directly that edge
is too.
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 klaus.schliep@gmail.com
## 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 SH.test(sp) ## End(Not run)