CensSpatial is an R package for analyzing spatial censored data through linear models. It offers a set of tools for simulating, estimating, making predictions, and performing local influence diagnostics for outlier detection. The package provides four algorithms for estimation and prediction. One of them is based on the stochastic approximation of the EM (SAEM) algorithm, which allows easy and fast estimation of the parameters of linear spatial models when censoring is present. The package provides worthy measures to perform diagnostic analysis using the Hessian matrix of the completed log-likelihood function. This work is divided into two parts. The first part discusses and illustrates the utilities that the package offers for estimating and predicting spatial censored data. The second one describes the valuable tools to perform diagnostic analysis. Several examples in spatial environmental data are also provided.
翻译:通过线性模型分析空间审查数据的R套件,用于通过线性模型分析空间审查数据,提供一套模拟、估计、预测和进行局部影响诊断的工具,用于外部探测。这套套件提供了四种估算和预测的算法,其中一种以EM(SAEM)算法的随机近似值为基础,便于在进行检查时简单和快速地估计线性空间模型的参数。这套套件提供了利用已完成的日志相似函数的赫森矩阵进行诊断分析的有价值的措施。这项工作分为两部分。第一部分讨论并说明了该套件为估计和预测空间审查数据提供的效用。第二套说明进行诊断分析的宝贵工具。还提供了空间环境数据的一些实例。