Local shape matrix
This computes a matrix formalising 'local shape', i.e., aggregated
standardised variance/covariance in a Mahalanobis neighbourhood of the data
points. This can be used for finding clusters when used as one of the
covariance matrices in
Invariant Coordinate Selection (function ics
in package
ICS
), see Hennig's
discussion and rejoinder of Tyler et al. (2009).
localshape(xdata,proportion=0.1,mscatter="mcd",mcdalpha=0.8, covstandard="det")
xdata |
objects times variables data matrix. |
proportion |
proportion of points to be considered as neighbourhood. |
mscatter |
"mcd" or "cov"; specified minimum covariance determinant or classical covariance matrix to be used for Mahalanobis distance computation. |
mcdalpha |
if |
covstandard |
one of "trace", "det" or "none", determining by what constant the pointwise neighbourhood covariance matrices are standardised. "det" makes the affine equivariant, as noted in the discussion rejoinder of Tyler et al. (2009). |
The local shape matrix.
Tyler, D. E., Critchley, F., Duembgen, L., Oja, H. (2009) Invariant coordinate selection (with discussion). Journal of the Royal Statistical Society, Series B, 549-592.
options(digits=3) data(iris) localshape(iris[,-5],mscatter="cov")
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