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, ...)

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.

Arguments

x: 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.

Author

Ramon Diaz-Uriarte and Theodore Garland, Jr.

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

data(SimulExample)
ex1.prcomp <- prcomp.phylog(SimulExample[,-11]) # 11th col. is a factor
options(digits=5)
ex1.prcomp
summary(ex1.prcomp)
plot(ex1.prcomp)

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