backfit {shapes} | R Documentation |
Backfit from scores to configuration
Description
Backfit from PNSS or PCA scores to a representative configuration
Usage
backfit(scores, x, type="pnss", size=1)
Arguments
scores |
n x p matrix of scores |
x |
An object that is the output of either pnss3d (if type="pnss") or procGPA (if type="pca") |
type |
Either "pnss" for PNSS or "pca" for PCA |
size |
The centroid size of the backfitted configuration. The default is 1 but one can rescale the backfitting if desired. |
Value
A k x m matrix of co-ordinates of the backfitted configuration
Author(s)
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( macf.dat, sphere.type="BIC", n.pc=8)
y <- backfit( ans$PNS$scores[1,] , ans ,type="pnss")
riemdist( macf.dat[,,1] , y ) #should be close to zero
ans2 <- procGPA( macf.dat, tangentcoords="partial")
y <- backfit( ans2$scores[1,] , ans2 ,type="pca")
riemdist( macf.dat[,,1] , y ) #should be close to zero
[Package shapes version 1.2.7 Index]