New statistical model for misreported data

• Autores: David Moriña Soler , Amanda Fernández Fontelo, Alejandra Cabaña , Pere Puig Casado
• Localización: Proceedings of the 35th International Workshop on Statistical Modelling : July 20-24, 2020 Bilbao, Basque Country, Spain / Itziar Irigoien Garbizu (ed. lit.) , Dae-Jin Lee (ed. lit.) , Joaquín Martínez Minaya (ed. lit.), María Xosé Rodríguez Álvarez (ed. lit.), 2020, ISBN 978-84-1319-267-3, págs. 169-174
• Idioma: inglés
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• Resumen

  • The main goal of this work is to present a new model able to deal with potentially misreported continuous time series. The proposed model is able to handle the autocorrelation structure in continuous time series data, which might be misreported. Its performance is illustrated through a real data application on COVID-19 disease in a chinese province, and a comprehensive simulation study is also discussed.