dimhat {spatstat} | R Documentation |
Given the kernel matrix that characterises a central subspace, this function estimates the dimension of the subspace.
dimhat(M)
M |
Kernel of subspace. A symmetric, non-negative definite, numeric
matrix, typically obtained from |
This function computes the maximum descent estimate of
the dimension of the central subspace with a given kernel matrix M
.
The matrix M
should be the kernel matrix of a central subspace,
which can be obtained from sdr
. It must be a symmetric,
non-negative-definite, numeric matrix.
The algorithm finds the eigenvalues lambda[1] ≥ ...≥ lambda[n] of M, and then determines the index k for which lambda[k]/lambda[k-1] is greatest.
A single integer giving the estimated dimension.
Matlab original by Yongtao Guan, translated to R by Suman Rakshit.
Guan, Y. and Wang, H. (2010) Sufficient dimension reduction for spatial point processes directed by Gaussian random fields. Journal of the Royal Statistical Society, Series B, 72, 367–387.