DANCo exploits the balanced information of both the normalized nearest neighbor distances as well as the angles of data pairs in the neighboring points.

est.danco(X, k = 5)

## Arguments

X

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

k

the neighborhood size used for estimating local intrinsic dimension.

## Value

a named list containing containing

estdim

estimated dimension via the method.

## References

Ceruti C, Bassis S, Rozza A, Lombardi G, Casiraghi E, Campadelli P (2014). “DANCo: An Intrinsic Dimensionality Estimator Exploiting Angle and Norm Concentration.” Pattern Recognition, 47(8), 2569--2581.

## Examples

# \donttest{
## create 3 datasets of intrinsic dimension 2.
X1 = aux.gensamples(n=50, dname="swiss")
X2 = aux.gensamples(n=50, dname="ribbon")

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

## print the results
line1 = paste0("* est.danco : 'swiss'  estiamte is ",round(out1$estdim,2)) line2 = paste0("* est.danco : 'ribbon' estiamte is ",round(out2$estdim,2))
line3 = paste0("* est.danco : 'saddle' estiamte is ",round(out3\$estdim,2))
cat(paste0(line1,"\n",line2,"\n",line3))
#> * est.danco : 'swiss'  estiamte is 2
#> * est.danco : 'ribbon' estiamte is 2
#> * est.danco : 'saddle' estiamte is 2
# }