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Editors-in-chief: Bettina GrĂ¼n, Edzer Pebesma & Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Multidimensional Scaling Using Majorization: SMACOF in R | de Leeuw | Journal of Statistical Software
Authors: Jan de Leeuw, Patrick Mair
Title: Multidimensional Scaling Using Majorization: SMACOF in R
Abstract: In this paper we present the methodology of multidimensional scaling problems (MDS) solved by means of the majorization algorithm. The objective function to be minimized is known as stress and functions which majorize stress are elaborated. This strategy to solve MDS problems is called SMACOF and it is implemented in an R package of the same name which is presented in this article. We extend the basic SMACOF theory in terms of configuration constraints, three-way data, unfolding models, and projection of the resulting configurations onto spheres and other quadratic surfaces. Various examples are presented to show the possibilities of the SMACOF approach offered by the corresponding package.

Page views:: 8742. Submitted: 2008-11-28. Published: 2009-08-04.
Paper: Multidimensional Scaling Using Majorization: SMACOF in R     Download PDF (Downloads: 8773)
smacof_1.0-0.tar.gz: R source package Download (Downloads: 1083; 537KB) v31i03.R: R example code from the paper Download (Downloads: 1125; 1KB)

DOI: 10.18637/jss.v031.i03

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.