inlabru: Spatial Inference using Integrated Nested Laplace Approximation
Version 2.1.9

Facilitates spatial modeling using integrated nested Laplace approximation via the INLA package (). Additionally, implements a log Gaussian Cox process likelihood for modeling univariate and spatial point processes based on ecological survey data. See Yuan Yuan, Fabian E. Bachl, Finn Lindgren, David L. Borchers, Janine B. Illian, Stephen T. Buckland, Havard Rue, Tim Gerrodette (2017), .

Getting started

Package details

AuthorFabian E. Bachl [aut, cre] (Fabian Bachl wrote the main code), Finn Lindgren [aut] (<https://orcid.org/0000-0002-5833-2011>, Finn Lindgren wrote code for SPDE posterior plotting, and continued development of the main code), David L. Borchers [ctb] (David Borchers wrote code for Gorilla data import and sampling, multiplot tool), Daniel Simpson [ctb] (Daniel Simpson wrote the basic LGCP sampling method), Lindesay Scott-Howard [ctb] (Lindesay Scott-Howard provied MRSea data import code)
Date of publication2018-07-24 09:20:03 UTC
MaintainerFabian E. Bachl <[email protected]>
LicenseGPL (>= 2)
Version2.1.9
URL http://www.inlabru.org
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("inlabru")

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inlabru documentation built on July 25, 2018, 1:04 a.m.