Open Conference Systems, 50th Scientific meeting of the Italian Statistical Society

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Spatial heterogeneity in principal component analysis: a study of deprivation index on Italian provinces
Paolo Postiglione, M. Simona Andreano, Roberto Benedetti, Alfredo Cartone

Last modified: 2018-05-25


Principal Component Analysis (PCA) is a tool often used for the construction of composite indicators even at the local level ([18]). In general, when we are dealing with spatial data, the method of PCA, in its classical version, is not appropriate for the synthesis of simple indicators. The objective of this paper is to introduce a method to take into account the spatial heterogeneity in PCA, extending the contribution introduced by [19]. The proposed method will be implemented for the definition of a deprivation index on Italian provinces.


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