论文标题
电球时期：用于圆形数据的空间和时空建模的R包装
CircSpaceTime: an R package for spatial and spatio-temporal modeling of Circular data
论文作者
论文摘要
CircspeTime是当前唯一可以实现贝叶斯模型用于圆形数据的空间和时空插值的R软件包。这些数据通常是在涉及许多风向，动物运动方向和波动方向的应用中发现的。为了分析此类数据，我们需要在位置s和时间t观察的模型，作为所谓的地统计模型，提供假定在距离和时间衰减的结构化依赖性。我们采用的方法首先是在空间和时间上为线性变量定义的高斯过程。然后，我们使用包装或投影来获取循环数据的过程。这些模型被铸造为层次结构，并在贝叶斯框架内具有拟合和推断。总的来说，该包装实现了由一系列论文开发的作品。最相关的是Jona Lasinio，Gelfand和Jona Lasinio（2012）； Wang and Gelfand（2014）; Mastrantonio，Jona Lasinio和Gelfand（2016）。所有过程均使用RCPP编写。估计值是通过MCMC获得的，允许并行多个链运行。在研究论文中采用的简单例程上，提出的模型的实施大大改善了。作为原始的跑步示例，对于空间和时空设置，我们在意大利中部使用风向数据集。
CircSpaceTime is the only R package currently available that implements Bayesian models for spatial and spatio-temporal interpolation of circular data. Such data are often found in applications where, among the many, wind directions, animal movement directions, and wave directions are involved. To analyze such data we need models for observations at locations s and times t, as the so-called geostatistical models, providing structured dependence assumed to decay in distance and time. The approach we take begins with Gaussian processes defined for linear variables over space and time. Then, we use either wrapping or projection to obtain processes for circular data. The models are cast as hierarchical, with fitting and inference within a Bayesian framework. Altogether, this package implements work developed by a series of papers; the most relevant being Jona Lasinio, Gelfand, and Jona Lasinio (2012); Wang and Gelfand (2014); Mastrantonio, Jona Lasinio, and Gelfand (2016). All procedures are written using Rcpp. Estimates are obtained by MCMC allowing parallelized multiple chains run. The implementation of the proposed models is considerably improved on the simple routines adopted in the research papers. As original running examples, for the spatial and spatio-temporal settings, we use wind directions datasets over central Italy.
