mvMORPH (version 1.2.1)

ancestral: Estimation of traits ancestral states.

Description

Reconstruct the ancestral states at each node of a phylogenetic tree from models fit obtained using the mvgls function. For models of the class mvXX this is a wrapper to the function estim

Usage

ancestral(object, ...)

Value

a matrix of reconstructed ancestral states for each node (note that the numerotation of the ancestral states starts at "N+1" [for the root], where N is the number of species in the tree)

Arguments

object

A model fit object obtained by the mvgls function.

...

Further options to be passed through. For instance, if a regression model is used, values for the predictor(s) at each node of the tree should be given in a matrix to the newdata argument. If a model of the type mvXX is used, the argument tree and data should be provided like in estim function.

Author

J. Clavel

Details

ancestral is an S3 method that reconstruct the ancestral states at each nodes of a phylogenetic tree from the models fit obtained by the mvgls function (Clavel et al. 2019). Ancestral states are estimated using generalized least squares (GLS; Martins & Hansen 1997, Cunningham et al. 1998 ). Note that when a regression model (rather than an intercept only model of the form Y~1) is provided, an argument "newdata" with a matrix of regressor values for each node should be provided (similar to what is done in the "predict" function).

References

Clavel, J., Aristide, L., Morlon, H., 2019. A Penalized Likelihood framework for high-dimensional phylogenetic comparative methods and an application to new-world monkeys brain evolution. Syst. Biol. 68: 93-116.

Cunningham C.W., Omland K.E., Oakley T.H. 1998. Reconstructing ancestral character states: a critical reappraisal. Trends Ecol. Evol. 13:361-366.

Martins E.P., Hansen T.F. 1997. Phylogenies and the comparative method: a general approach to incorporating phylogenetic information into the analysis of interspecific data. Am. Nat. 149:646-667.

See Also

mvgls, estim, predict.mvgls

Examples

# \donttest{

set.seed(1)
n <- 32 # number of species
p <- 5 # number of traits

tree <- pbtree(n=n, scale=1) # phylogenetic tree
R <- crossprod(matrix(runif(p*p), ncol=p)) # a random covariance matrix
# simulate a BM dataset
Y <- mvSIM(tree, model="BM1", nsim=1, param=list(sigma=R, theta=rep(0,p))) 
data=list(Y=Y)

fit <- mvgls(Y~1, data=data, tree, model="BM", method="LL")

# Perform the ancestral states reconstruction
anc <- ancestral(fit)

# retrieve the ancestral states
head(anc)

# }