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

2020/03/20 by David Moriña, Moriña, David, Amanda Fernández‐Fontelo +5
Mathematics · #Applications (stat.AP) #FOS: Computer and information sciences #Methodology (stat.ME) #Statistical Methods and Inference

paper · pdf · doi:10.48550/arxiv.2003.09202

openalex publication_date 2020/03/20 · openalex created_date 2022/07/26 · openalex updated_date 2026/07/28

Abstract

The main goal of this work is to present a new model able to deal with\npotentially misreported continuous time series. The proposed model is able to\nhandle the autocorrelation structure in continuous time series data, which\nmight be partially or totally underreported or overreported. Its performance is\nillustrated through a comprehensive simulation study considering several\nautocorrelation structures and two real data applications on human\npapillomavirus incidence in Girona (Catalunya, Spain) and COVID-19 incidence in\nthe Chinese region of Heilongjiang.\n

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