est.nearneighbor2 | R Documentation |
Though similar to est.nearneighbor1
, authors of the reference
argued that there exists innate bias in the method and proposed a non-iterative algorithm
to reflect local distance information under a range of neighborhood sizes.
est.nearneighbor2(X, kmin = 2, kmax = max(3, round(ncol(X)/2)))
X |
an (n\times p) matrix or data frame whose rows are observations. |
kmin |
minimum neighborhood size, larger than 1. |
kmax |
maximum neighborhood size, smaller than p. |
a named list containing containing
estimated intrinsic dimension.
Kisung You
verveer_evaluation_1995Rdimtools
## create an example data with intrinsic dimension 2 X = cbind(aux.gensamples(dname="swiss"),aux.gensamples(dname="swiss")) ## acquire an estimate for intrinsic dimension output = est.nearneighbor2(X) sprintf("* est.nearneighbor2 : estimated dimension is %.2f.",output$estdim)
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