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Spatial Data Analysis with INLA

Spatial Data Analysis with INLA


This session will show how to fit mixed-effects models to spatial lattice data using the integrated nested Laplace approximation with the R-INLA package. This will cover some standard models such as the conditionally autoregressive (CAR) specification. The examples will be illustrated using the New York leukemia dataset and a few hints on how to produce maps to display the results will be given as well.

Room 7.3.J06. Campus de Leganés, Av. de la Universidad, 30, 28911 Leganés, Madrid, Spain.


The following CRAN packages are required:

pkgs <- c("sp", "spdep", "maptools", "rgdal", "gstat", "DClusterm", "spData")
pkgs <- c(pkgs, "viridis", "RColorBrewer")
pkgs <- c(pkgs, "tmap")


INLA is also required, but it is not available on CRAN:

install.packages("INLA", repos = "https://inla.r-inla-download.org/R/stable")

About the speaker

Virgilio Gómez-Rubio is an associate professor in the Department of Mathematics, Universidad de Castilla-La Mancha (Albacete, Spain). He has developed several packages on spatial and Bayesian statistics that are available on CRAN, as well as co-authored books on spatial data analysis and INLA.