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.