pnss3d: Principal Nested Shape Space Analysis

In iandryden/shapes: Statistical Shape Analysis

Principal Nested Shape Space Analysis

Description

Approximation of Principal Nested Shapes Spaces using PCA: 2D or 3D data, small or large samples

Usage

pnss3d(x,sphere.type="seq.test",mean.type="Frechet",alpha = 0.1,R = 100,
                        nlast.small.sphere = 1,n.pc="Full",output=TRUE)

Arguments

x	k x m x n array of landmark data.
sphere.type	a character string specifying the type of sphere fitting method. "seq.test" specifies sequential tests to decide either "small" or "great"; "small" specifies Principal Nested SMALL Sphere; "great" specifies Principal Nested GREAT Sphere (radius pi/2); "BIC" specifies BIC statistic to decide either "small" or "great"; and "bi.sphere" specifies Principal Nested GREAT Sphere for the first part and Principal Nested SMALL Sphere for the last part. The default is "seq.test".
mean.type	a character string specifying the type of circular mean calculation at the last stage. "Frechet" specifies the Frechet mean on a circle; "Fisher" specifies the Fisher mle a.k.a. resultant mean.
alpha	significance level (0 < alpha < 1) used when sphere.type = "seq.test". The default is 0.1.
R	the number of bootstrap samples to be evaluated for the sequential test. The default is 100.
nlast.small.sphere	the number of small spheres in the finishing part used when sphere.type = "bi.sphere".
n.pc	the number of PC scores to be used (n.pc >= 2). The default "Full" is to use all PCs.
output	Logical. If TRUE then plots and some brief printed summaries are given. If FALSE then no plots or output is given.

Value

A list with components

PNS	the output of the function pns
GPAout	the result of GPA
spheredata	transformed spherical data from the PC scores
percent	proportion of variances explained.

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, plot3darcs

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")

iandryden/shapes documentation built on April 17, 2025, 1:57 p.m.