Multidimensional Scaling Using Majorization : SMACOF in

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.

[1]  C H COOMBS,et al.  Psychological scaling without a unit of measurement. , 1950, Psychological review.

[2]  G. Ekman Dimensions of Color Vision , 1954 .

[3]  Leonard M. Blumenthal,et al.  Theory and applications of distance geometry , 1954 .

[4]  H. D. Brunk,et al.  AN EMPIRICAL DISTRIBUTION FUNCTION FOR SAMPLING WITH INCOMPLETE INFORMATION , 1955 .

[5]  N. L. Johnson,et al.  Multivariate Analysis , 1958, Nature.

[6]  Joseph L. Zinnes,et al.  Theory and Methods of Scaling. , 1958 .

[7]  R. Shepard The analysis of proximities: Multidimensional scaling with an unknown distance function. II , 1962 .

[8]  G. Forsythe,et al.  On the Stationary Values of a Second-Degree Polynomial on the Unit Sphere , 1965 .

[9]  W J Levelt,et al.  Triadic comparisons of musical intervals. , 1966, The British journal of mathematical and statistical psychology.

[10]  Dato N. de Gruijter The cognitive structure of Dutch political parties in 1966 , 1967 .

[11]  Werner Dinkelbach On Nonlinear Fractional Programming , 1967 .

[12]  L. Guttman A general nonmetric technique for finding the smallest coordinate space for a configuration of points , 1968 .

[13]  J. Chang,et al.  Analysis of individual differences in multidimensional scaling via an n-way generalization of “Eckart-Young” decomposition , 1970 .

[14]  Paul E. Green,et al.  Applied multidimensional scaling : a comparison of approaches and algorithms , 1972 .

[15]  P. Schönemann,et al.  An algebraic solution for a class of subjective metrics models , 1972 .

[16]  Emil Spjøtvoll A Note on a Theorem of Forsythe and Golub , 1972 .

[17]  J. M. Bremner,et al.  Statistical Inference under Restrictions , 1973 .

[18]  R. Shepard Representation of structure in similarity data: Problems and prospects , 1974 .

[19]  Moonja P. Kim,et al.  The Method of Sorting as a Data-Gathering Procedure in Multivariate Research. , 1975, Multivariate behavioral research.

[20]  Forrest W. Young,et al.  Nonmetric individual differences multidimensional scaling: An alternating least squares method with optimal scaling features , 1977 .

[21]  D. Rubin,et al.  Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper , 1977 .

[22]  Jan de Leeuw,et al.  Correctness of Kruskal's algorithms for monotone regression with ties , 1977 .

[23]  D. G. Weeks,et al.  Restricted multidimensional scaling models , 1978 .

[24]  R N Shepard,et al.  Multidimensional Scaling, Tree-Fitting, and Clustering , 1980, Science.

[25]  I. Borg,et al.  A model and algorithm for multidimensional scaling with external constraints on the distances , 1980 .

[26]  Horst Knörrer,et al.  Geodesics on the ellipsoid , 1980 .

[27]  J. Ramsay Some Statistical Approaches to Multidimensional Scaling Data , 1982 .

[28]  Graham K. Rand,et al.  Quantitative Applications in the Social Sciences , 1983 .

[29]  Jan de Leeuw,et al.  A special Jackknife for Multidimensional Scaling , 1986 .

[30]  J. Leeuw Convergence of the majorization method for multidimensional scaling , 1988 .

[31]  T. Cox,et al.  Multidimensional scaling on a sphere , 1991 .

[32]  J. Meulman The integration of multidimensional scaling and multivariate analysis with optimal transformations , 1992 .

[33]  Patrick J. F. Groenen,et al.  The majorization approach to multidimensional scaling : some problems and extensions , 1993 .

[34]  A. Gifi,et al.  NONLINEAR MULTIVARIATE ANALYSIS , 1990 .

[35]  Jan de Leeuw,et al.  Block-relaxation Algorithms in Statistics , 1994 .

[36]  P. D. Tao Lagrangian Stability and Global Optimality in Nonconvex Quadratic Minimization Over Euclidean Balls and Spheres , 1995 .

[37]  M. B. Tabanov New ellipsoidal confocal coordinates and geodesics on an ellipsoid , 1996 .

[38]  P. Groenen,et al.  The tunneling method for global optimization in multidimensional scaling , 1996 .

[39]  Rasmus Bro,et al.  MULTI-WAY ANALYSIS IN THE FOOD INDUSTRY Models, Algorithms & Applications , 1998 .

[40]  P. Groenen,et al.  Modern Multidimensional Scaling: Theory and Applications , 1999 .

[41]  J. Tenenbaum,et al.  A global geometric framework for nonlinear dimensionality reduction. , 2000, Science.

[42]  J. Leeuw Applications of Convex Analysis to Multidimensional Scaling , 2000 .

[43]  S T Roweis,et al.  Nonlinear dimensionality reduction by locally linear embedding. , 2000, Science.

[44]  A. Perelomov,et al.  A note on geodesics on ellipsoid , 2002, math-ph/0203032.

[45]  Chun-Houh Chen,et al.  INTERACTIVE DIAGNOSTIC PLOTS FOR MULTIDIMENSIONAL SCALING WITH APPLICATIONS IN PSYCHOSIS DISORDER DATA ANALYSIS , 2000 .

[46]  Trevor F. Cox,et al.  Metric multidimensional scaling , 2000 .

[47]  Nicholas I. M. Gould,et al.  Trust Region Methods , 2000, MOS-SIAM Series on Optimization.

[48]  Ron Kimmel,et al.  Texture Mapping via Spherical Multi-dimensional Scaling , 2005, Scale-Space.

[49]  R. Steele,et al.  Optimization , 2005, Encyclopedia of Biometrics.

[50]  J. Leeuw Accelerated Least Squares Multidimensional Scaling , 2006 .

[51]  J. Leeuw,et al.  Simple and Canonical Correspondence Analysis Using the R Package anacor , 2007 .

[52]  P. Legendre,et al.  vegan : Community Ecology Package. R package version 1.8-5 , 2007 .

[53]  Sarah C. Goslee,et al.  The ecodist Package for Dissimilarity-based Analysis of Ecological Data , 2007 .

[54]  Alexander M. Bronstein,et al.  Fast Multidimensional Scaling using Vector Extrapolation , 2008 .

[55]  Christian Buchta,et al.  Distance and Similarity Measures , 2015, Encyclopedia of Multimedia.

[56]  Patrick Mair,et al.  Multidimensional Scaling Using Majorization: SMACOF in R , 2008 .

[57]  J. Leeuw POLYNOMIAL EXTRAPOLATION TO ACCELERATE FIXED POINT ITERATIONS , 2008 .

[58]  Jan de Leeuw,et al.  Gifi Methods for Optimal Scaling in R: The Package homals , 2009 .