A modified CANDECOMP method for fitting the extended INDSCAL model |
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Authors: | Geert De Soete J Douglas Carroll Anil D Chaturvedi |
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Institution: | (1) Department of Data Analysis, University of Ghent, Henri Dunantlaan 2, B-9000 Ghent, Belgium;(2) Graduate School of Management, Rutgers University, University Heights, 92 New Street, 07102-1895, New Jersey, Newark |
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Abstract: | A modified CANDECOMP algorithm is presented for fitting the metric version of the Extended INDSCAL model to three-way proximity
data. The Extended INDSCAL model assumes, in addition to the common dimensions, a unique dimension for each object. The modified
CANDECOMP algorithm fits the Extended INDSCAL model in a dimension-wise fashion and ensures that the subject weights for the
common and the unique dimensions are nonnegative. A Monte Carlo study is reported to illustrate that the method is fairly
insensitive to the choice of the initial parameter estimates. A second Monte Carlo study shows that the method is able to
recover an underlying Extended INDSCAL structure if present in the data. Finally, the method is applied for illustrative purposes
to some empirical data on pain relievers. In the final section, some other possible uses of the new method are discussed.
Geert De Soete is supported as “Bevoegdverklaard Navorser” of the Belgian “Nationaal Fonds voor Wetenschappelijik Onderzoek”. |
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Keywords: | Extended INDSCAL model Extended Euclidean distance model CANDECOMP Alternating least squares method Constrained INDSCAL model |
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