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A Compositional approach for modelling SDG7 indicators

Authors: Marcillo Delgado, Juan Carlos;

A Compositional approach for modelling SDG7 indicators

Abstract

Al igual que en otros sectores, los indicadores de seguimiento del sector de la energía tienen, en muchos casos, carácter composicional, característica clave para la correcta modelación de tendencias y proyecciones, ver Pérez-Foguet et al. (2017). La investigación actual se centra en el seguimiento del acceso a energía, específicamente en la modelización composicional de la evolución temporal del indicador acceso a electricidad, utilizando la adaptación de tres técnicas: Regresión lineal (LM), Modelos aditivos generalizados (GAM) y Support Vector Machine (SVM).

Country
Spain
Keywords

SDG7, Trend analysis, :Matemàtiques i estadística::Estadística matemàtica [Àrees temàtiques de la UPC], Àrees temàtiques de la UPC::Matemàtiques i estadística::Estadística matemàtica, Estadística matemàtica--Aplicacions, Compositional data analysis, :62 Statistics::62P Applications [Classificació AMS], Mathematical Statistics -- Applications, Electricity access, Classificació AMS::62 Statistics::62P Applications

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selected citations
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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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