shapepca {shapes} | R Documentation |
Provides graphical summaries of principal components for shape.
shapepca(proc, pcno = c(1, 2, 3), type = "r", mag = 1, joinline = c(1, 1), project=c(1,2))
proc |
List given by the output from procGPA() |
pcno |
A vector of the PCs to be plotted |
type |
Options for the types of plot for the $m=2$ planar case:
"r" : rows along PCs evaluated at c = -3,0,3 sd's along PC,
"v" : vectors drawn from mean to +3 sd's along PC,
"s" : plots along c= -3, -2, -1, 0, 1, 2, 3 superimposed,
"m" : movie backward and forwards from -3 to +3 sd's along PC,
"g" : TPS grid from mean to +3 sd's along PC.
|
mag |
Magnification of the effect of the PC (scalar multiple of sd's) |
joinline |
A vector stating which landmarks are joined up by lines, e.g. joinline=c(1:n,1) will start at landmark 1, join to 2, ..., join to n, then re-join to landmark 1. |
project |
The default orthogonal projections if in higher than 2 dimensions |
For $m=3$ the mean and PCs are plotted with orthogonal projections.
No value is returned
Ian Dryden
Dryden, I.L. and Mardia, K.V. (1998) Statistical Shape Analysis. Wiley, Chichester.
procGPA
#2d example data(gorf.dat) data(gorm.dat) gorf<-procGPA(gorf.dat) gorm<-procGPA(gorm.dat) shapepca(gorf,type="r",mag=3) shapepca(gorf,type="v",mag=3) shapepca(gorm,type="r",mag=3) shapepca(gorm,type="v",mag=3) #3D example #data(macm.dat) #out<-procGPA(macm.dat) #movie #shapepca(out,pcno=1)