ProcGPA {Morpho}

Workhorse function for procSym, responsible for Procrustes registration

Description

Workhorse function for procSym, responsible for Procrustes registration

Usage

ProcGPA(
  dat.array,
  tol = 1e-05,
  scale = TRUE,
  CSinit = FALSE,
  silent = TRUE,
  weights = NULL,
  centerweight = FALSE,
  reflection = TRUE,
  pcAlign = TRUE
)

Arguments

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.

Value

returns a list with

rotated

k x m x n array of the rotated configurations

mshape

sample meanshape

Author(s)

Stefan Schlager

References

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.

See Also

procSym, rotonto

Examples

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)