inlabru: Spatial Inference using Integrated Nested Laplace Approximation
Version 2.1.3

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 <[email protected]> (main code), Finn Lindgren <[email protected]> (SPDE posterior plotting), David L. Borchers <[email protected]> (Gorilla data import and sampling, multiplot tool), Daniel Simpson <[email protected]> (basic LGCP sampling method), Lindesay Scott-Hayward <[email protected]@st-andrews.ac.uk> (MRSea data import)
Date of publication2018-02-11 14:26:23 UTC
MaintainerFabian E. Bachl <[email protected]>
LicenseGPL (>= 2)
Version2.1.3
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 Feb. 11, 2018, 3:12 p.m.