proc.weight: calculate weights inverse to the distances from the specified...

In Morpho: Calculations and Visualisations Related to Geometric Morphometrics

calculate weights inverse to the distances from the specified observation.

Description

for calculation of a shape model by averaging the observations neighbouring the configuration in question, it is necessary to calculate weights by similarity.

Usage

proc.weight(
  data,
  number,
  ref,
  report = TRUE,
  reg = 0,
  log = FALSE,
  mahalanobis = FALSE,
  weightfun = NULL
)

Arguments

data	array containing landmark configurations
number	integer: how many of the neighbours are to be involved.
ref	integer: position in the array that is used as reference.
report	logical: require report about name of the reference.
reg	numeric: regularise mahalanobis distance by adding reg to the diagonal of eigenvalues of the covariance matrix.
log	logical: use the logarithm of the distances.
mahalanobis	logical: use mahalanobis distance.
weightfun	custom function that operates on a vector of distances (see examples) and generates weights accordingly.

Details

distances of zero will get a weight of 1e12 (this is scaled to all weights summing to one), thus weights for observations further away are converging to zero.

Value

data	dataframe containing id, procrustes/mahalanobis distance and weight according to the reference
reference	returns observations' names if available
rho.all	dataframe containing distances to references of all observations

Examples

if (require(shapes)) {
proc <- procSym(gorf.dat)
##get weights for the the four specimen closest to the first observation.
weights <- proc.weight(proc$rotated,4,1)

##estimate the first specimen by weighted neighbour shapes.
estim <- proc$mshape*0;
for (i in 1:4)
{estim <-estim+proc$rotated[,,weights$data$nr[i]]*weights$data$weight[i]}

### visualise
plot(estim,asp=1)## show estimation
points(proc$rotated[,,1],col=3)##show original

## use a gaussian smoother to compute weights using a bandwidth of 0.05
gaussWeight <- function(r,sigma=0.05) {
   sigma <- 2*sigma^2
   return(exp(-r^2/ sigma))
}
weights <- proc.weight(proc$rotated,4,1,weightfun=gaussWeight)
}

Morpho documentation built on June 22, 2024, 7:19 p.m.