ProcGPA | R Documentation |
Workhorse function for procSym, responsible for Procrustes registration
ProcGPA(
dat.array,
tol = 1e-05,
scale = TRUE,
CSinit = FALSE,
silent = TRUE,
weights = NULL,
centerweight = FALSE,
reflection = TRUE,
pcAlign = TRUE
)
dat.array |
Input k x m x n real array, where k is the number of points, m is the number of dimensions, and n is the sample size. |
tol |
numeric: Threshold for convergence during iterative superimpositioning. |
scale |
logical: indicating if scaling is requested |
CSinit |
logical: if TRUE, all configurations are initially scaled to Unit Centroid Size. |
silent |
logical: suppress output of elapsed time. |
weights |
numeric vector: assign per landmark weights. |
centerweight |
logical: if TRUE, the landmark configuration is scaled according to weights during the rotation process, instead of being scaled to the Centroid size. |
reflection |
logical: allow reflections. |
pcAlign |
logical: if TRUE, the shapes are aligned by the principal axis of the first specimen, otherwise the orientation of the first specimen is used. |
returns a list with
rotated |
k x m x n array of the rotated configurations |
mshape |
sample meanshape |
Stefan Schlager
Goodall C. 1991. Procrustes methods in the statistical analysis of shape. Journal of the Royal Statistical Society. Series B. Statistical Methodology 53:285-239.
Dryden IL, Mardia KV. 1998. Statistical shape analysis. John Wiley and sons, Chichester.
procSym, rotonto
data(boneData)
proc <- ProcGPA(boneLM, CSinit=TRUE, silent=TRUE)
#now we landmarks 5 - 9 double the weight as the others
weights <- c(rep(1,4),rep(2,5),1)
proc.wt <- ProcGPA(boneLM, CSinit=TRUE, weights=weights, silent=TRUE)
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