ancThresh | R Documentation |
This function uses Bayesian MCMC to estimate ancestral states and thresholds for a discrete character under the threshold model from quantitative genetics (Felsenstein 2012).
ancThresh(tree, x, ngen=100000, sequence=NULL, method="mcmc", model=c("BM","OU","lambda"), control=list(), ...)
tree |
phylogenetic tree. |
x |
a named vector containing discrete character states; or a matrix containing the tip species, in rows, and probabilities of being in each state, in columns. |
ngen |
number of generations to run the MCMC. |
sequence |
assumed ordering of the discrete character state. If not supplied and |
method |
only method currently available is |
model |
model for the evolution of the liability. Options are |
control |
list containing the following elements: |
... |
additional arguments to be passed to |
print
and plot
S3 methods are now available for the object class "ancThresh"
.
This function returns an object of class "ancThresh"
containing the posterior sample from our analysis, although with other components.
Liam Revell liam.revell@umb.edu
Felsenstein, J. (2012) A comparative method for both discrete and continuous characters using the threshold model. American Naturalist, 179, 145-156.
Revell, L. J. (2014) Ancestral character estimation under the threshold model from quantitative genetics. Evolution, 68, 743-759.
anc.Bayes
, threshBayes
## Not run: ## load data from Revell & Collar (2009) data(sunfish.tree) data(sunfish.data) ## extract character of interest fmode<-setNames(sunfish.data$feeding.mode, rownames(sunfish.data)) ## run MCMC mcmc<-ancThresh(sunfish.tree,fmode,ngen=1000000) ## plot results plot(mcmc,mar=c(0.1,0.1,4.1,0.1)) title(main="Posterior probabilities for node states", font.main=3) ## End(Not run)
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