NNshapeReg | R Documentation |
Estimate the shape of one set of landmarks by averaging the shape of the nearest neighbours obtained by a second set of landmarks. Weights are calculated either form Mahalanobis or Procrustes distances. This can be useful for data with missing landmarks.
NNshapeReg(
x,
y = NULL,
n = 3,
mahalanobis = FALSE,
mc.cores = parallel::detectCores()
)
x |
an array or matrix (one row per specim) with data used for estimating weights. |
y |
an array or matrix (one row per specim) with landmark data on which the weighted averaging is applied for prediction. If NULL, x will be used for both tasks. |
n |
amount of nearest neighbours to consider |
mahalanobis |
logical: use mahalanobis distance |
mc.cores |
integer: amount of cores used for parallel processing. |
This function calculates weights from one set of shape data and then estimates the shape of another (or same) set of landmarks. CAUTION: landmark data has to be registered beforehand.
matrix or array of estimates.
proc.weight
, fixLMtps
if (require(shapes)) {
proc <- procSym(gorf.dat)
#use the closest 3 specimen based on the first 4 landmarks
#to estimate the shape
estim <- NNshapeReg(proc$rotated[1:4,,],proc$rotated,n=3,mc.cores=1)
#compare estimation and true config
plot(proc$rotated[,,1],asp=1)
points(estim[,,1],col=2)
}
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