The R-package GeoAdjust https://github.com/umut-altay/GeoAdjust-package implements fast empirical Bayesian geostatistical inference for household survey data from the Demographic and Health Surveys Program (DHS) using Template Model Builder (TMB). DHS household survey data is an important source of data for tracking demographic and health indicators, but positional uncertainty has been intentionally introduced in the GPS coordinates to preserve privacy. GeoAdjust accounts for such positional uncertainty in geostatistical models containing both spatial random effects and raster- and distance-based covariates. The R package supports Gaussian, binomial and Poisson likelihoods with identity link, logit link, and log link functions respectively. The user defines the desired model structure by setting a small number of function arguments, and can easily experiment with different hyperparameters for the priors. GeoAdjust is the first software package that is specifically designed to address positional uncertainty in the GPS coordinates of point referenced household survey data. The package provides inference for model parameters and can predict values at unobserved locations.
翻译:本文介绍了R包GeoAdjust https://github.com/umut-altay/GeoAdjust-package,该包使用模板模型构建器(TMB)实现了快速的经验贝叶斯地统计推断,支持来自人口和健康调查项目(DHS)的家庭调查数据。 DHS家庭调查数据是跟踪人口和健康指标的重要数据来源,但故意引入了GPS坐标的位置不确定性以保护隐私。 GeoAdjust在包含空间随机效应和栅格和距离为基础的协变量的地统计模型中考虑这种位置的不确定性。该R包支持具有恒等链,logit链和log链函数的高斯,二项式和泊松似然函数。用户通过设置少量函数参数来定义所需的模型结构,并可以轻松尝试不同的超参数。GeoAdjust是第一个专门设计用于解决点参考家庭调查数据GPS坐标的位置不确定性的软件包。该软件包提供了对模型参数的推断,并可以在未观测到的位置上预测值。