plot3darcs: Modes of variation plots for PCA and PNSS

In shapes: Statistical Shape Analysis

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")

shapes documentation built on Feb. 16, 2023, 8:16 p.m.