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EloSteepness is a package that allows estimating
steepness of dominance hierarchies from interaction networks. It does so
by estimating Bayesian Elo-ratings, from which the steepness metric can
be calculated. The major difference from classic approaches is that we
obtain posterior steepness distributions, not point estimates.
More details on the theoretical background can be found in the
accompanying paper
(preprint is here).
Below are the instructions to install EloSteepness.
In order to get the package up and running you need a fairly recent
version of R (I’d recommend at least v4.0). You also need a working
installation of rstan.
Since the package is on CRAN now, installation should be easy with a
simple call to:
install.packages("EloSteepness")
This also should take care of installing all necessary dependencies,
including Stan. If you run the following code and it
results in a figure, you are good to go.
library("EloSteepness")
data(dommats, package = "EloRating")
# using small numbers for iterations etc to speed up running time
set.seed(123)
res <- elo_steepness_from_matrix(dommats$elephants, n_rand = 3, cores = 2,
iter = 1000, warmup = 500,
refresh = 0, chains = 2, seed = 1)
plot_steepness(res)
summary(res)If this failed, you can try the following: The easiest way of
installing Stan is to install
the brms package. (brms is not actually
required for EloSteepness to work, but it handles the
installation of rstan and friends very conveniently.) If
you don’t want to deal with brms, you can also try to
install rstan by itself (see
here for instructions). If you already have brms (or
rstan) then you are probably good to go. If not, then
execute the following command and if asked for whether you want to
install packages from source select ‘no’ (unless you know what
you are doing of course).
install.packages("brms")
The only other thing you need are two more packages,
EloRating and aniDom, which are easy to
install:
install.packages("EloRating")
install.packages("aniDom")
For good measure, it might be good idea to restart R (or RStudio if you work with it) at this point. If you want to be on the safe side, you’d even restart your computer at this point, but this shouldn’t be necessary in most cases.
With this done, you can install EloSteepness. There are
two ways of doing that. Depending on the level of experience with R, I
would recommend option 1 only to more advanced users and option 2 to
novices.
For this to work you’ll need the devtools package (which
you can get via install.packages("devtools")). Also
required is a working package building tool chain. To check whether this
is available run:
devtools::has_devel()If that gives positive feedback then you are set. If not, you need to
install more stuff (on MacOS you need the Xcode command
line tools (e.g. here), and
on Windows the Rtools here).
I’ve also seen cases where problems arose because the version of
devtools was outdated, so even if you have it installed
already it might be a good idea to update the package (also with
install.packages("devtools")).
Next, you need to decide whether or not you want to build the vignettes alongside installing the package.
In order to make the tutorial accessible from within R, you need two
more things: \(\LaTeX\) and
pandoc. The easiest way of getting the former done (unless
you have it already) is to use:
install.packages("tinytex")
tinytex::install_tinytex()
tinytex:::install_yihui_pkgs()Next, install pandoc. If
you are using RStudio you can skip this latter step
(pandoc comes with RStudio), and proceed directly to:
devtools::install_github("gobbios/EloSteepness", build_vignettes = TRUE, dependencies = TRUE)This will take several minutes.
To check whether the installation worked, restart R/RStudio and try to open the tutorial that comes with the package.
vignette("tutorial", package = "EloSteepness")If you are happy with downloading the tutorial manually here, things should be a little simpler:
devtools::install_github("gobbios/EloSteepness", build_vignettes = FALSE)This still might take several minutes to complete.
Here you download the package as a single file and then install it from there. Start by downloading the package file from here.
If you are on Windows, download the
EloSteepness_0.4.6.zip file and run (and don’t forget to
change the path and use the correct file name):
install.packages("C:/Users/myname/Downloads/EloSteepness_0.4.6.zip",
dependencies = TRUE,
repos = NULL, type = "win.binary")If you are on MacOS, download the EloSteepness_0.4.6.tgz
file and run (and don’t forget to change the path and use the correct
file name):
install.packages("~/Downloads/EloSteepness_0.4.6.tgz",
dependencies = TRUE,
repos = NULL, type = "mac.binary")Depending on your hardware, this can take up to several minutes to complete. After this is done, I would again recommend to restart R.
To check whether the installation worked, try to open the tutorial.
vignette("tutorial", package = "EloSteepness")If this didn’t work or you feel a bit more adventurous, choose the
file EloSteepness_0.4.6.tar.gz for download (don’t unpack
it!), and remember the path you saved it to… Then depending on what OS
you use, adapt to your needs and run one of the following code chunks
(don’t forget to change the path and use the correct file name):
# something like this on MacOS or Linux
install.packages("~/Downloads/EloSteepness_0.4.6.tar.gz",
repos = NULL, type = "source")# something like this on Windows
install.packages("C:/Users/myname/Downloads/EloSteepness_0.4.6.tar.gz",
repos = NULL, type = "source")And finally, if you are just interested in the tutorial, you can find it here.
Please refer to the tutorial to go through some examples. Either download
it here or use
vignette("tutorial", package = "EloSteepness") to launch it
directly from R.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.