论文标题
使用R套餐夏季的时空调查结果平滑
Space-Time Smoothing of Survey Outcomes using the R Package SUMMER
论文作者
论文摘要
复杂的调查数据的可用性不断提高，以及以良好的空间和时间尺度估算人口统计和健康指标的持续需求，这导致了数据稀疏性问题，这导致需要时空平滑方法，这些方法承认收集数据的方式。开源R包夏季实现了各种调查数据的空间或时空平滑的方法。重点是小区域估计。我们主要关注低收入国家和中等收入国家环境中的指标。我们的方法对于来自人口健康调查和多个指标群集调查的数据特别有用。我们以调查包中的功能为基础，并使用inla进行快速贝叶斯计算。本文包括对这些方法的简要概述，并说明了访问和处理调查的工作流程，估计了次国儿童死亡率以及通过模拟数据和DHS调查可视化结果。
The increasing availability of complex survey data, and the continued need for estimates of demographic and health indicators at a fine spatial and temporal scale, which leads to issues of data sparsity, has led to the need for spatio-temporal smoothing methods that acknowledge the manner in which the data were collected. The open source R package SUMMER implements a variety of methods for spatial or spatio-temporal smoothing of survey data. The emphasis is on small-area estimation. We focus primarily on indicators in a low and middle-income countries context. Our methods are particularly useful for data from Demographic Health Surveys and Multiple Indicator Cluster Surveys. We build upon functions within the survey package, and use INLA for fast Bayesian computation. This paper includes a brief overview of these methods and illustrates the workflow of accessing and processing surveys, estimating subnational child mortality rates, and visualizing results with both simulated data and DHS surveys.
