| plot3darcs {shapes} | R Documentation |
Modes of variation plots for PCA and PNSS
Description
Modes of variation plots for PCA and PNSS based on 3D views and arcs along a mode. c * sd : the extent along lower and upper principal arcs.
The lower principal arc -> 0 -> upper principal arc has a total of 2*nn+1 configurations with: nn configurations along the negative principal arc to 0; one configuration at the PNS mean; nn configurations along the positive principal arc.
Usage
plot3darcs(x,pcno=1,c=1,nn=100,boundary.data=TRUE,view.theta=0,view.phi=0,type="pnss")
Arguments
x |
Output from pnss3d |
pcno |
The number of the PC/PNSS component. The default is 1, the first PC/PNSS |
c |
Number of standard deviations along each arc |
nn |
In total 2 * nn + 1 configurations: n configurations on arc from negative to 0; 1 configuration at 0; nn configurations from 0 to positive |
boundary.data |
Logical for whether to use boundary data or not. |
view.theta |
Viewing angle theta |
view.phi |
Viewing angle phi |
type |
"pnss" principal nested sphere mean and arc, or "pca" Procrustes mean and linear PC. |
Value
A list with components
PNSmean |
the PNSS mean |
lu.arc |
the configurations along the arc |
Author(s)
Kwang-Rae Kim, Ian Dryden
References
Dryden, I.L., Kim, K., Laughton, C.A. and Le, H. (2019). Principal nested shape space analysis of molecular dynamics data. Annals of Applied Statistics, 13, 2213-2234.
Jung, S., Dryden, I.L. and Marron, J.S. (2012). Analysis of principal nested spheres. Biometrika, 99, 551-568.
See Also
pns, pns4pc, pnss3d
Examples
ans <- pnss3d(digit3.dat, sphere.type="BIC", n.pc=5)
#aa <- plot3darcs(ans,c=2,pcno=1)
#bb <- plot3darcs(ans,c=2,pcno=1,type="pca")