pcaOtpmPointwiseDimEst {intrinsicDimension}

Dimension Estimation With Optimally Topology Preserving Maps

Description

Intrinsic dimension estimation with the method proposed in Bruske and Sommer (1998). A graph called optimally topology preserving map (OTPM) is constructed and on this local PCA is made with the Fukunaga-Olsen criterion to determine which eigenvalues that are significant.

Usage

 pcaOtpmPointwiseDimEst(data, N, alpha = .05) 

Arguments

data

a data set for which dimension should be estimated.

N

the number of the nodes in the OTPM.

alpha

the significance level for the Fukunaga-Olsen method.

Value

A DimEstPointwise object, inheriting data.frame, with two columns:

dim.est

The dimension estimate at each point.

nbr.nb

The number of neighboring nodes used for the dimension estimate at each point.

Author(s)

Kerstin Johnsson, Lund University

References

Bruske, J. and Sommer, G. (1998) Intrinsic dimensionality estimation with optimally topology preserving maps. IEEE Trans. on Pattern Anal. and Mach. Intell., 20(5), 572-575.

See Also

pcaLocalDimEst

Examples

data <- hyperBall(1000, 5)
pcaOtpmPointwiseDimEst(data, 400)