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Convergence of the sequence of parameters generated by alternating least squares algorithms

Convergence of the sequence of parameters generated by alternating least squares algorithms

Samenvatting

Several models in data analysis are estimated by minimizing the objective function defined as the residual sum of squares between the model and the data. A necessary and sufficient condition for the existence of a least squares estimator is that the objective function attains its infimum at a unique point. It is shown that the objective function for Parafac-2 need not attain its infimum, and that of DEDICOM, constrained Parafac-2, and, under a weak assumption, SCA and Dynamals do attain their infimum. Furthermore, the sequence of parameter vectors, generated by an alternating least squares algorithm, converges if it decreases the objective function to its infimum which is attained at one or finitely many points.

OrganisatieHanzehogeschool Groningen
LectoraatStatistical Techniques for Applied Research
Gepubliceerd inComputational statistics and data analysis Elsevier, Vol. 51, Uitgave: 2, Pagina's: 481-489
Datum2006-11-15
TypeArtikel
ISSN0167-9473
DOI10.1016/j.csda.2005.09.003
TaalEngels

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