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arXiv 2003.092022020-03stat.MEstat.AP

New statistical model for misreported data with application to current public health challenges

David Moriña, Amanda Fernández-Fontelo, Alejandra Cabaña, Pedro Puig

英文摘要：

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 partially or totally underreported or overreported. Its performance is illustrated through a comprehensive simulation study considering several autocorrelation structures and two real data applications on human papillomavirus incidence in Girona (Catalunya, Spain) and COVID-19 incidence in the Chinese region of Heilongjiang.

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