Introduction
This is the home page for the following review:
Eglen SJ (2016) Bivariate spatial point patterns in the retina: a reproducible review. Journal de la Société Française de Statistique 157:33–48. PDF
This package contains all the material needed to regenerate the article for itself. Some key parts of the package are:
- vignettes/eglen2015.Rnw: the source file for the article in LaTeX format.
- inst/extdata: a folder containing all the data files studied in this article.
Recompiling the paper
This R package depends on a few other packages, from CRAN and my personal library. The following sequence should install everything you need:
Rscript -e 'install.packages(c("splancs", "spatstat", "devtools", "knitr", "xtable", "tinytex"))'
Rscript -e 'install.packages(c("sjedmin", "sjedrp", "sjevor","sjedist"), type="source", contriburl="http://damtp.cam.ac.uk/user/eglen/r/")'
Rscript -e 'devtools::install_github("sje30/eglen2015",build_vignettes=TRUE)'
The last line should load this package. Once it is installed, you can then view the paper, or view the knitr document that created the paper:
vignette("eglen2015")
eglen2015:::edit()
This does of course assume that your system already has R, latex, and various unix tools. That may not be the case; however, you can still use the package through the Docker system, see next.
Docker
Once you have docker installed on your system, you can download and run this package using:
docker run -d -p 8787:8787 sje30/eglen2015
(View sje30/eglen2015 to check the status of this Docker package.)
Then visit the web page to start R (username and password are "rstudio"):
http://localhost:8787/ ## linux
http://192.168.99.100:8787/ ## mac, windows users
The IP address for mac/windows may vary; you can check it by running the command:
docker-machine ip default
Once you have logged in, you can then do the following commands to recompile the document:
setwd("eglen2015/vignettes/")
source("run.R")
Then examine the vignettes
folder and you should see
eglen2015.pdf
.
Thanks to the Rocker team for the R-based docker images, on which this work is based.