GPA: Generalised Procrustes Analysis of configurations

Description Usage Arguments Value See Also

Description

Given a number of (2D) configurations, this function uses a combination of transformations (reflections, rotations, translations and scaling) to find a 'consensus' configuration which best matches all the component configurations in a least-squares sense.

Usage

1
GPA(X, scale = TRUE)

Arguments

X

a list of dissimilarity matrices

scale

boolean flag indicating if the transformation should include the scaling operation

Value

a two column vector with the coordinates of the group configuration

See Also

procrustes



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