Rdimtools (version 1.0.0)

est.packing: Intrinsic Dimension Estimation using Packing Numbers

Description

Instead of covering numbers which are expensive to compute in many fractal-based methods, est.packing exploits packing numbers as a proxy to describe spatial density. Since it involves random permutation of the dataset at each iteration, every run might have different results.

Usage

est.packing(X, eps = 0.01)

Arguments

X

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

eps

small positive number for stopping threshold.

Value

a named list containing containing

estdim

estimated intrinsic dimension.

References

kegl_intrinsic_2002Rdimtools

Examples

# NOT RUN {
## create 'swiss' roll dataset
X = aux.gensamples(dname="swiss")

## try different eps values
out1 = est.packing(X, eps=0.1)
out2 = est.packing(X, eps=0.01)
out3 = est.packing(X, eps=0.001)

## print the results
sprintf("* est.packing : estimated dimension with eps=0.1   is %.2f.",out1$estdim)
sprintf("* est.packing : estimated dimension with eps=0.01  is %.2f.",out2$estdim)
sprintf("* est.packing : estimated dimension with eps=0.001 is %.2f.",out3$estdim)
# }
# NOT RUN {
# }