cmdscale_lanczos: Faster multi-dimensional scaling

In refunders/refund: Regression with Functional Data

Faster multi-dimensional scaling

Description

This is a modified version of cmdscale that uses the Lanczos procedure (slanczos) instead of eigen. Called by smooth.construct.pco.smooth.spec.

Usage

cmdscale_lanczos(d, k = 2, eig = FALSE, add = FALSE, x.ret = FALSE)

Arguments

d	a distance structure as returned by dist, or a full symmetric matrix of distances or dissimilarities.
k	the maximum dimension of the space which the data are to be represented in; must be in {1, 2, ..., n-1}.
eig	logical indicating whether eigenvalues should be returned.
add	logical indicating if the additive constant of Cailliez (1983) should be computed, and added to the non-diagonal dissimilarities such that the modified dissimilarities are Euclidean.
x.ret	indicates whether the doubly centred symmetric distance matrix should be returned.

Value

as cmdscale

Author(s)

David L Miller, based on code by R Core.

References

Cailliez, F. (1983). The analytical solution of the additive constant problem. Psychometrika, 48, 343-349.

See Also

smooth.construct.pco.smooth.spec

refunders/refund documentation built on March 20, 2024, 7:11 a.m.