A rendered (html) version of this book is available here. The pdf version has been submitted to CRC/Chapman and Hall, for hardcopy publication.
To recreate/reproduce this book:
- git clone this repository
- download the data used in Ch 13 from https://uni-muenster.sciebo.de/s/8mEbeHPOX9GdAYn, and extract the contents of the
aqsubdirectory intosdsr/aq - install all R packages listed under Dependencies
- install quarto
- run
quarto render --to html
See also the Dockerfile; building the image with
docker build . -t sdsr --build-arg TZ=`timedatectl show --property=Timezone | awk -F = '{print $2}'`
and running it with
docker run -d -p 80:80 sdsr:latest
will serve the html book on http://localhost:80
To locally process the book, install the following R packages from CRAN:
install.packages(c(
"dbscan",
"gstat",
"hglm",
"igraph",
"lme4",
"lmtest",
"maps",
"mapview",
"matrixStats",
"mgcv",
"R2BayesX",
"rgeoda",
"rnaturalearth",
"rnaturalearthdata",
"sf",
"spatialreg",
"spdep",
"spData",
"stars",
"tidyverse",
"tmap"))
Install INLA:
install.packages("INLA", repos = c(getOption("repos"), INLA="https://inla.r-inla-download.org/R/stable"))
Install spDataLarge:
options(timeout = 600); install.packages("spDataLarge", repos = "https://nowosad.github.io/drat/",type = "source")
Install starsdata:
options(timeout = 600); install.packages("starsdata", repos = "http://pebesma.staff.ifgi.de", type = "source")
Install sf and stars from source from github (not needed after sf 1.0-9 and stars 0.5-7 are available from CRAN):
# apt-get install -y libudunits2-dev libgdal-dev libgeos-dev libproj-dev
install.packages("remotes")
remotes::install_github("r-spatial/sf")
remotes::install_github("r-spatial/stars")
or as binary from r-universe:
options(repos = c(
rspatial = "https://r-spatial.r-universe.dev",
CRAN = "https://cloud.r-project.org"))
install.packages(c("sf", "stars"))
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