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  • 1
    Electronic Resource
    Electronic Resource
    Springer
    Journal of classification 12 (1995), S. 57-71 
    ISSN: 1432-1343
    Keywords: Weighted Euclidean model ; INDSCAL ; Multidimensional scaling ; Specificities ; Monotone splines
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract The INDSCAL individual differences scaling model is extended by assuming dimensions specific to each stimulus or other object, as well as dimensions common to all stimuli or objects. An “alternating maximum likelihood” procedure is used to seek maximum likelihood estimates of all parameters of this EXSCAL (Extended INDSCAL) model, including parameters of monotone splines assumed in a “quasi-nonmetric” approach. The rationale for and numerical details of this approach are described and discussed, and the resulting EXSCAL method is illustrated on some data on perception of musical timbres.
    Type of Medium: Electronic Resource
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  • 2
    Electronic Resource
    Electronic Resource
    Springer
    Journal of classification 6 (1989), S. 105-119 
    ISSN: 1432-1343
    Keywords: Individual differences ; Multidimensional scaling ; Rational starting configuration ; INDSCAL
    Source: Springer Online Journal Archives 1860-2000
    Topics: Mathematics
    Notes: Abstract Five different methods for obtaining a rational initial estimate of the stimulus space in the INDSCAL model were compared using the SINDSCAL program for fitting INDSCAL. The effect of the number of stimuli, the number of subjects, the dimensionality, and the amount of error on the quality and efficiency of the final SINDSCAL solution were investigated in a Monte Carlo study. We found that the quality of the final solution was not affected by the choice of the initialization method, suggesting that SINDSCAL finds a global optimum regardless of the initialization method used. The most efficient procedures were the methods proposed by by de Leeuw and Pruzansky (1978) and by Flury and Gautschi (1986) for the simultaneous diagonalization of several positive definite symmetric matrices, and a method based on linearly constraining the stimulus space using the CANDELINC approach developed by Carroll, Pruzansky, and Kruskal (1980).
    Type of Medium: Electronic Resource
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  • 3
    ISSN: 1860-0980
    Keywords: Cluster Analysis ; Trees
    Source: Springer Online Journal Archives 1860-2000
    Topics: Psychology
    Notes: Abstract A least-squares algorithm for fitting ultrametric and path length or additive trees to two-way, two-mode proximity data is presented. The algorithm utilizes a penalty function to enforce the ultrametric inequality generalized for asymmetric, and generally rectangular (rather than square) proximity matrices in estimating an ultrametric tree. This stage is used in an alternating least-squares fashion with closed-form formulas for estimating path length constants for deriving path length trees. The algorithm is evaluated via two Monte Carlo studies. Examples of fitting ultrametric and path length trees are presented.
    Type of Medium: Electronic Resource
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  • 4
    ISSN: 1860-0980
    Keywords: Cluster Analysis ; Variable Importance
    Source: Springer Online Journal Archives 1860-2000
    Topics: Psychology
    Notes: Abstract In the application of clustering methods to real world data sets, two problems frequently arise: (a) how can the various contributory variables in a specific battery be weighted so as to enhance some cluster structure that may be present, and (b) how can various alternative batteries be combined to produce a single clustering that “best” incorporates each contributory set. A new method is proposed (SYNCLUS, SYNthesizedCLUStering) for dealing with these two problems.
    Type of Medium: Electronic Resource
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