论文标题
使用Inlautils的R-Inla软件包的图形输出和空间交叉验证
Graphical outputs and Spatial Cross-validation for the R-INLA package using INLAutils
论文作者
论文摘要
统计分析通过模型拟合和检查的迭代过程进行。 R-INLA软件包通过比其他MCMC方法快得多的速度拟合许多贝叶斯模型来促进此迭代。由于对贝叶斯分析的结果和模型对象的解释可能很复杂，因此R软件包Inlautils为用户提供了易于访问，清晰和可自定义的图形摘要，该图形摘要来自R- Inla。此外，它提供了一个功能，可用于执行和可视化空间丢弃的交叉验证（SLOOCV）方法的结果，该方法可用于比较多个空间模型的预测性能。在本文中，我们描述并说明了（1）图形摘要绘图函数和（2）SlooCV方法的使用。我们通过确定方法的局限性并讨论未来的潜在改进来结束本文。
Statistical analyses proceed by an iterative process of model fitting and checking. The R-INLA package facilitates this iteration by fitting many Bayesian models much faster than alternative MCMC approaches. As the interpretation of results and model objects from Bayesian analyses can be complex, the R package INLAutils provides users with easily accessible, clear and customisable graphical summaries of model outputs from R- INLA. Furthermore, it offers a function for performing and visualizing the results of a spatial leave-one-out cross-validation (SLOOCV) approach that can be applied to compare the predictive performance of multiple spatial models. In this paper, we describe and illustrate the use of (1) graphical summary plotting functions and (2) the SLOOCV approach. We conclude the paper by identifying the limits of our approach and discuss future potential improvements.
