inlabru: an R package for Bayesian spatial modelling from ecological survey data

Bachl, F. E., Lindgren, F., Borchers, D. L. and Illian, J. B. (2019) inlabru: an R package for Bayesian spatial modelling from ecological survey data. Methods in Ecology and Evolution, 10(6), pp. 760-766. (doi:10.1111/2041-210X.13168)

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Abstract

1. 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. 2. 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). 3. 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. 4. 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.

Item Type:Articles
Additional Information:This research was funded by EPSRC grants EP/K041061/1, EP/K041053/1 and EP/K041053/2.
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Illian, Professor Janine
Authors: Bachl, F. E., Lindgren, F., Borchers, D. L., and Illian, J. B.
College/School:College of Science and Engineering > School of Mathematics and Statistics > Statistics
Journal Name:Methods in Ecology and Evolution
Publisher:Wiley
ISSN:2041-210X
ISSN (Online):2041-210X
Published Online:24 February 2019

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