| project.pca | R Documentation | 
Projects data onto principal components.
project.pca(data, pca, angular = FALSE, fit = FALSE, ...)
z2xyz.pca(z.coord, pca)
xyz2z.pca(xyz.coord, pca)
data | 
 a numeric vector or row-wise matrix of data to be projected.  | 
pca | 
  an object of class   | 
angular | 
 logical, if TRUE the data to be projected is treated as torsion angle data.  | 
fit | 
  logical, if TRUE the data is first fitted to   | 
... | 
  other parameters for   | 
xyz.coord | 
 a numeric vector or row-wise matrix of data to be projected.  | 
z.coord | 
 a numeric vector or row-wise matrix of PC scores (i.e. the z-scores which are centered and rotated versions of the origional data projected onto the PCs) for conversion to xyz coordinates.  | 
A numeric vector or matrix of projected PC scores.
Karim ElSawy and Barry Grant
Grant, B.J. et al. (2006) Bioinformatics 22, 2695–2696.
pca.xyz, pca.tor, fit.xyz 
## Not run: 
attach(transducin)
gaps.pos <- gap.inspect(pdbs$xyz)
#-- Do PCA without structures 2 and 7
pc.xray <- pca.xyz(pdbs$xyz[-c(2,7), gaps.pos$f.inds])
#-- Project structures 2 and 7 onto the PC space
d <- project.pca(pdbs$xyz[c(2,7), gaps.pos$f.inds], pc.xray)
plot(pc.xray$z[,1], pc.xray$z[,2],col="gray")
points(d[,1],d[,2], col="red")
detach(transducin)
## End(Not run)
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