condMDSeigen {cml}

Conditional Multidimensional Scaling With Closed-Form Solution

Description

Provides a closed-form solution for conditional multidimensional scaling, based on multiple linear regression and eigendecomposition.

Usage

condMDSeigen(d, V, u.dim, method = c('matrix', 'vector'))

Arguments

d

a dist object of N entities.

V

an Nxq matrix of q manifold auxiliary parameter values of the N entities.

u.dim

the embedding dimension.

method

if matrix, there are no restrictions for the B matrix . If vector, the B matrix is restricted to be diagonal.

Value

U

the embedding result.

B

the estimated B matrix.

eig

the computed eigenvalues.

stress

the corresponding normalized conditional stress value of the solution.

Author(s)

Anh Tuan Bui

References

Bui, A. T. (2022). A Closed-Form Solution for Conditional Multidimensional Scaling. Pattern Recognition Letters 164, 148-152. https://doi.org/10.1016/j.patrec.2022.11.007

See Also

condMDS, condIsomap

Examples

# see help(cml)