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Assessing uncertainty of voter transitions estimated from aggregated data. Application to the 2017 French presidential election

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Assessing uncertainty of voter transitions estimated from aggregated data. Application to the 2017 French presidential election

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Romero, R.; Pavía, JM.; Martín Marín, J.; Romero, G. (2020). Assessing uncertainty of voter transitions estimated from aggregated data. Application to the 2017 French presidential election. Journal of Applied Statistics. 47(13-15):2711-2736. https://doi.org/10.1080/02664763.2020.1804842

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Título: Assessing uncertainty of voter transitions estimated from aggregated data. Application to the 2017 French presidential election
Autor: Romero, Rafael Pavía, Jose M. Martín Marín, Jorge Romero, Gerardo
Entidad UPV: Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat
Fecha difusión:
Resumen:
[EN] Inferring electoral individual behaviour from aggregated data is a very active research area, with ramifications in sociology and political science. A new approach based on linear programming is proposed to estimate ...[+]
Palabras clave: Ecological inference , Linear programming , Voter transitions , R x C contingency tables , French elections
Derechos de uso: Reserva de todos los derechos
Fuente:
Journal of Applied Statistics. (issn: 0266-4763 )
DOI: 10.1080/02664763.2020.1804842
Editorial:
Taylor & Francis
Versión del editor: https://doi.org/10.1080/02664763.2020.1804842
Código del Proyecto:
info:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/ECO2017-87245-R/ES/INNOVACION SOCIAL Y ECONOMICA, DESCIFRANDO LA FUNCION DE LA CULTURA Y LA COMUNICACION./
info:eu-repo/grantAgreement/GVA//AICO%2F2019%2F053/
Agradecimientos:
This piece of research has been supported by the Spanish Ministry of Science, Innovation and Universities and the Spanish Agency of Research, co-funded with FEDER funds, grant ECO2017-87245-R, and by Consellería d'Innovació, ...[+]
Tipo: Artículo

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