stratPCA {astrochron} | R Documentation |
Principal Component Analysis on Stratigraphic Series
Description
Perform principal component analysis on stratigraphic series.
Usage
stratPCA(dat,id=TRUE,rot=0,nPC=NULL,output=0,symSize=2,genplot=1)
Arguments
dat |
Your data frame; should be in stratigraphic order. First column may be location identifier (e.g., depth). Can contain any number of variables. |
id |
Is the first column of dat an ID column (depth/height/time)? (T or F) |
rot |
Rotation method. 0=none, 1=varimax (orthogonal), 2=promax (oblique) |
nPC |
Number of principal components to extract. Default=all |
output |
What would you like to output? 0=nothing, 1=PC loadings, 2=scores |
symSize |
Size of symbols used in color plots? Default=2 |
genplot |
Generate summary plots? (0) no plots, (1) standard plots, (2) additional plots |
Examples
## Not run:
# create a test data set, composed of 7 variables:
# antiphased 20 kyr cycles with noise,
# antiphased 40 kyr cycles with noise,
# antiphased 110 kyr cycles with noise,
# and a variable that is entirely noise
noise=0.01
a=cycles(1/20,noisevar=noise,genplot=FALSE)
b=cycles(1/20,phase=pi,noisevar=noise,genplot=FALSE)
c=cycles(1/40,noisevar=noise,genplot=FALSE)
d=cycles(1/40,phase=pi,noisevar=noise,genplot=FALSE)
e=cycles(1/110,noisevar=noise,genplot=FALSE)
f=cycles(1/110,phase=pi, noisevar=noise,genplot=FALSE)
g=ar1(npts=500,genplot=FALSE)
ex=data.frame(cbind(a[,1],a[,2],b[,2],c[,2],d[,2],e[,2],f[,2],g[,2]))
stratPCA(ex)
stratPCA(ex,rot=1,nPC=4)
stratPCA(ex,rot=2,nPC=4)
## End(Not run)
[Package astrochron version 1.3 Index]