Rdimtools (version 1.0.0)

est.mindkl: MiNDkl

Description

It is a minimum neighbor distance estimator of the intrinsic dimension based on Kullback Leibler divergence estimator.

Usage

est.mindkl(X, k = 5)

Arguments

X

an \((n\times p)\) matrix or data frame whose rows are observations.

k

the neighborhood size for defining locality.

Value

a named list containing containing

estdim

the global estimated dimension.

References

lombardi_minimum_2011Rdimtools

See Also

est.mindml

Examples

# NOT RUN {
## create 3 datasets of intrinsic dimension 2.
X1 = aux.gensamples(dname="swiss")
X2 = aux.gensamples(dname="ribbon")
X3 = aux.gensamples(dname="saddle")

## acquire an estimate for intrinsic dimension
out1 = est.mindkl(X1, k=10)
out2 = est.mindkl(X2, k=10)
out3 = est.mindkl(X3, k=10)

## print the results
sprintf("* est.mindkl : estimated dimension for 'swiss'  data is %.2f.",out1$estdim)
sprintf("* est.mindkl : estimated dimension for 'ribbon' data is %.2f.",out2$estdim)
sprintf("* est.mindkl : estimated dimension for 'saddle' data is %.2f.",out3$estdim)
# }
# NOT RUN {
# }