Classical Multi-Dimensional Scaling for a distance matrix

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Description

cmdsFit obtains coordinates in a k dimensional space which best approximate the given distances between objects.

Usage

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cmdsFit(d, k=2, type='classic', add=FALSE, cor.method='pearson')

Arguments

d

Distances between objects

k

Dimensionality of the reconstructed space, typically set to 2 or 3.

type

Set to "classic" to perform classical MDS (uses function cmdscale from package stats). Set to "isoMDS" to use Kruskal's non-metric MDS (uses function isoMDS from package MASS).

add

Logical indicating if an additive constant c* should be computed, and added to the non-diagonal dissimilarities such that all n-1 eigenvalues are non-negative in cmdscale

cor.method

A character string indicating which correlation coefficient (or covariance) is to be computed. One of "pearson" (default), "kendall", or "spearman", can be abbreviated.

Value

The function returns a cmdsFit object. See help("cmdsFit-class") for details.

Methods

signature(d = "matrix")

Use Classical Multi-Dimensional Scaling to represent points in a k-dimensional space.

Examples

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### Not run
#d <- matrix(c(0,5,10,5,0,15,10,15,0),byrow=TRUE,ncol=3)
#cmdsFit(d,add=TRUE)

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