论文标题
分解：用于贝叶斯空间分类建模的R包装
disaggregation: An R Package for Bayesian Spatial Disaggregation Modelling
论文作者
论文摘要
分解建模或降尺度已成为流行病学的重要学科。在大型地区汇总的监视数据越来越普遍，导致对建模框架的需求不断增长，这些框架可以处理这些数据以了解空间模式。分解回归模型使用在大型异源区域汇总的响应数据，通过使用细尺度协变量来告知异质性，以在该区域进行高尺度的预测。本文介绍了R软件包分解，该分解提供了简化用于精细预测的分解模型的过程。
Disaggregation modelling, or downscaling, has become an important discipline in epidemiology. Surveillance data, aggregated over large regions, is becoming more common, leading to an increasing demand for modelling frameworks that can deal with this data to understand spatial patterns. Disaggregation regression models use response data aggregated over large heterogenous regions to make predictions at fine-scale over the region by using fine-scale covariates to inform the heterogeneity. This paper presents the R package disaggregation, which provides functionality to streamline the process of running a disaggregation model for fine-scale predictions.
