论文标题
区域级时空泊松泊松混合模型用于预测域数和比例
Area-level spatio-temporal Poisson mixed models for predicting domain counts and proportions
论文作者
论文摘要
本文介绍了带有时间和SAR（1）空间相关的随机效应的区域级泊松混合模型。二分法变量比例和计数的小面积预测因素来自新模型，相应的平方误差是通过参数bootstrap估算的。本文说明了引入的方法，其中有两个应用程序对真实数据。第一个涉及2007 - 2008年加利西亚（西班牙）森林大火的数据，目标是建模和预测火灾的计数。第二个是对2013年加利西亚的西班牙生活条件调查的数据，目标是估计贫困线下的妇女县比例。
This paper introduces area-level Poisson mixed models with temporal and SAR(1) spatially correlated random effects. Small area predictors of the proportions and counts of a dichotomic variable are derived from the new models and the corresponding mean squared errors are estimated by parametric bootstrap. The paper illustrates the introduced methodology with two applications to real data. The first one deals with data of forest fires in Galicia (Spain) during 2007-2008 and the target is modeling and predicting counts of fires. The second one treats data from the Spanish living conditions survey of Galicia of 2013 and the target is the estimation of county proportions of women under the poverty line.
