Phylogenetic principal components analysis
This function performs phylogenetic PCA (e.g., Revell 2009; Evolution).
phyl.pca(tree, Y, method="BM", mode="cov", ...) ## S3 method for class 'phyl.pca' biplot(x, ...) scores(object, ...) ## S3 method for class 'phyl.pca' scores(object, ...)
tree |
phylogeny as an object of class |
Y |
data matrix with traits in columns. |
method |
method to obtain the correlation structure: can be |
mode |
is the mode for the PCA: can be |
x |
object of class |
object |
object of class |
... |
for S3 plotting method |
If method="lambda" then λ will be optimized on the interval (0,1) using optimize. Optimization method can be set using the option opt which can take values "ML", "REML", or "fixed". If the last of these is selected than the user should also specify a value of λ to use via the argument lambda.
S3 methods (print, summary, and biplot) are modified from code provided by Joan Maspons and are based on the same methods for objects of class "prcomp". Function biplot now permits the argument choices to be supplied, which should be a vector of length two indicated the two PC axes to be plotted.
S3 method scores extracts or computes (for a matrix of newdata) PC scores given an object of class "phyl.pca".
An object of class "phyl.pca" consisting of a list with some or all of the following components:
Eval |
diagonal matrix of eigenvalues. |
Evec |
matrix with eigenvectors in columns. |
S |
matrix with scores. |
L |
matrix with loadings. |
lambda |
fitted value of λ ( |
logL |
log-likelihood for λ model ( |
Liam Revell liam.revell@umb.edu, Joan Maspons
Revell, L. J. (2009) Size-correction and principal components for interspecific comparative studies. Evolution, 63, 3258-3268.
Revell, L. J. (2012) phytools: An R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol., 3, 217-223.
## load data from Mahler et al. (2010) data(anoletree) data(anole.data) ## run phylogenetic PCA anole.pca<-phyl.pca(anoletree,anole.data) print(anole.pca) ## plot results plot(anole.pca) biplot(anole.pca)
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