An Application of the Tensor-Based Approach to Mortality Modeling

Giovanni Cardillo (), Paolo Giordani (), Susanna Levantesi () and Andrea Nigri ()
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Giovanni Cardillo: Sapienza University, Department of Statistical Sciences
Paolo Giordani: Sapienza University, Department of Statistical Sciences
Susanna Levantesi: Sapienza University, Department of Statistical Sciences
Andrea Nigri: Bocconi University, Department of Social and Political Sciences

A chapter in Mathematical and Statistical Methods for Actuarial Sciences and Finance, 2022, pp 134-139 from Springer

Abstract: Abstract With the increasing availability of temporal data, researchers often analyze information stored in matrices, in which entries are replicated on different occasions. Such multidimensional data can be stored in 3-way arrays or tensors to be analyzed. A collection of 3-way arrays can also be available leading to 4-way arrays. In this work, we apply a tensor-based method, the Tucker4, to mortality data provided by the World Health Organization, referred to 4 dimensions (causes of death, age groups, years, and countries) and organized in a 4-way array. We carry out the analysis on the total population. Our findings reveal some peculiar aspects of the mortality phenomenon.

Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-3-030-99638-3_22

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DOI: 10.1007/978-3-030-99638-3_22

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