A copula-based clustering algorithm to analyse EU country diets
Authors: Di Lascio, M.F.L. and Disegna, M.
Publisher: Bournemouth University
Place of Publication: Bournemouth, UK
Abstract:The aim of the paper is to suggest a novel clustering technique to explore the changes of the food diet in 40 European countries in accordance with common European policies and guidelines on healthy diets and lifestyles.
The proposed clustering algorithm is based on copulas and it is called Co- Clust. The CoClust algorithm is able to find clusters according to the mul- tivariate dependence structure of the data generating process. The database analysed contains information on the proportions of calories from 16 food aggregates in 40 European countries observed over 40 years by the Food and Agriculture Organization of the United Nations (FAO). The findings suggest that European country diets are changing, individually or as a group, but not in a unique direction. Central and Eastern European countries are becoming unhealthier, while the tendency followed by the majority of the remaining countries is to integrate the common European guidelines on healthy, bal- anced, and diversified diets in their national policies.
https://eprints.bournemouth.ac.uk/26586/
https://repec.bmth.ac.uk/bam/wp/BAFES04.pdf
Source: BURO EPrints
