1,721,092 research outputs found

    Non-linear multi-block partial least squares via uni-variate and bivariate B-splines

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    In the last decade much effort has been spent modelling dependence among variables to probe the relationships between response variables and predictor ones observed at different occasions/spaces/times. In this paper we propose a non-linear generalization of mult-block Partial Least Squares using multivariate additive splines. We show the method performance on real sensory data sets

    Non symmetrical multiple correspondence analysis with linear constraints.

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    In the framework of the Multidimensional Data Analysis, Lauro and D’Ambra (1984) developed "Non Symmetrical Multiple Correspondence Analysis" (NSMCA) in order to study the dependence structure of a qualitative variable (criterion) from two or more qualitative variables (predictors) codified in a complete disjunctive form. From a geometrical point of view, NSMCA aims at finding out the best approximation of the categories of the criterion variable into the vectorial subspaces spanned by the categories of the explanatory variables taking into account the orthogonal decomposition: global inertia = explained inertia + residual inertia. In this paper, according to a further decomposition of the global inertia, an extension of NSMCA, which considers linear constraints, is developed

    Tensorial Co-Structure Analysis for the Full Multi Modules Customer Satisfaction Evaluation

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    In letteratura sono state proposte differenti tecniche per la valutazione della Customer Satisfaction (CS), spesso basate sul concetto di gap. In questo contributo, nel caso di più rilevazioni sulle stesse unità statistiche, viene proposta una strategia di analisi integrata che consente di scomporre l’analisi del gap tra qualità percepita ed attesa in ulteriori componenti da analizzare ai fini di un miglioramento del servizio
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