cmdsFit: Classical Multi-Dimensional Scaling for a distance matrix

In htSeqTools: Quality Control, Visualization and Processing for High-Throughput Sequencing data

Description

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

Usage

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

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

htSeqTools documentation built on May 6, 2019, 3:39 a.m.