prcomp.phylog: Principal Components Analysis from Simulated Data Sets

Description

Performs a principal component analyses on a set of simulated data and return the eigenvalues.

Usage

# S3 method for phylog
prcomp(x, max.num=0, exclude.tips=NULL, lapply.size=100,
              center=TRUE, scale=TRUE, ...)

Arguments

the columns from a data set returned from read.sim.data that you want to use in the PCA. The first column MUST be sim.counter and the second Tips.

max.num

if different from 0, the maximum number of simulations to analyze.

exclude.tips

an optional vector giving the names of tips to exclude from the analyses.

lapply.size

a tuning parameter that can affect the speed of calculations; see Details in phylog.lm.

center

should the data be centered before analyses? defaults to yes; see prcomp.

scale

should the data be scaled before the analyses? defaults to yes; see prcomp.

...

Not used.

Value

A list (of class phylog.prcomp) with components

call

the call to the function

Eigenvalues

all the eigenvalues from the PCA. The one with sim.counter=0 corresponds to the original (''real'') data.

References

Diaz-Uriarte, R., and Garland, T., Jr., in prep. PHYLOGR: an R package for the analysis of comparative data via Monte Carlo simulations and generalized least squares approaches.

Krzanowski, W. J. (1990) Principles of multivariate analysis Oxford University Press.

Morrison, D. F. (1990) Multivariate statistcal methods, 3rd ed. McGraw-Hill.

Examples

Run this code

# NOT RUN {
data(SimulExample)
ex1.prcomp <- prcomp.phylog(SimulExample[,-11]) # 11th col. is a factor
options(digits=5)
ex1.prcomp
summary(ex1.prcomp)
plot(ex1.prcomp)
# }