论文标题
针对当前公共卫生挑战的应用的新数据统计模型的新统计模型
New statistical model for misreported data with application to current public health challenges
论文作者
论文摘要
这项工作的主要目的是提出一个新的模型，能够处理潜在的连续时间序列。所提出的模型能够处理连续时间序列数据中的自相关结构，这些数据可能部分或完全不足或过度报告。通过一项全面的仿真研究来说明其性能，考虑到吉罗纳（Girona）（西班牙卡塔卢尼亚（Catalunya））和海伦吉安（Heilongjiang）中国地区的吉罗纳（Catalunya，西班牙卡塔卢尼亚（Catalunya））的两个人乳头瘤病毒发病率的两种真实数据应用。
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.
