inlabru: an R package for Bayesian spatial modelling from ecological survey data
inlabru: an R package for Bayesian spatial modelling from ecological survey data
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DOI：
10.1111/2041-210x.13168
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发表时间：
2019-06-01
影响因子：
6.6
通讯作者：
Illian, Janine B.
中科院分区：
文献类型：
--
作者：
Bachl, Fabian E.;Lindgren, Finn;Illian, Janine B.
空间过程是许多生态过程的核心，但将空间相关性与生态调查数据相结合的拟合模型在计算上具有挑战性。这对于点模式数据（其中主要数据是发现目标物种的位置）尤其如此，但对于网格化数据和来自连续空间场的地理参考样本也是如此。我们在这里描述了R包inlabru，它建立在广泛使用的RINLA包的基础上，使用集成的嵌套拉普拉斯近似（INLA，芸香et al.，2009年）。该软件包提供了拟合空间密度面和估计丰度以及绘图和预测的方法。它可容纳点、计数、地理参考样本或距离采样数据。本文描述了该软件包的主要功能，通过对spatstat软件包中包含的大猩猩巢数据（Baddeley，& Turner，2005），dsm软件包中包含的线样带调查数据集（米勒，Rexstad，Burt，Bravington，&赫德利，2018）以及模拟连续空间场的地理参考样本进行拟合模型来说明。
Spatial processes are central to many ecological processes, but fitting models that incorporate spatial correlation to data from ecological surveys is computationally challenging. This is particularly true of point pattern data (in which the primary data are the locations at which target species are found), but also true of gridded data, and of georeferenced samples from continuous spatial fields. We describe here the R package inlabru that builds on the widely used RINLA package to provide easier access to Bayesian inference from spatial point process, spatial count, gridded, and georeferenced data, using integrated nested Laplace approximation (INLA, Rue et al., 2009). The package provides methods for fitting spatial density surfaces and estimating abundance, as well as for plotting and prediction. It accommodates data that are points, counts, georeferenced samples, or distance sampling data. This paper describes the main features of the package, illustrated by fitting models to the gorilla nest data contained in the package spatstat (Baddeley, & Turner, 2005), a line transect survey dataset contained in the package dsm (Miller, Rexstad, Burt, Bravington, & Hedley, 2018), and to a georeferenced sample from a simulated continuous spatial field.