Precompiling your Stan programs

[bgoodri]

It is good to see another package on CRAN making use of Stan! But for packages like bmlm that offer a fixed set of Stan models, it is preferable to compile them when the package is built for several reasons:

1. The vast majority of users --- who are installing binary packages from CRAN for Windows or Mac --- would not need to first install a C++ toolchain in order to use bmlm. Only people who install packages from source would need the C++ toolchain and they probably already have one.
2. Users would not have to wait 30 -- 60 seconds for the models to start running.
3. It is somewhat more robust to updates to StanHeaders on CRAN.

The easiest way to do this is to call rstan::rstan.package.skeleton("skeleton") when the working directory is /tmp or something and copy the contents of /tmp/skeleton into your local clone of bmlm. This is how the rstanarm, beanz, and eggCounts R packages work. Ultimately, there will be a list called stanmodels in the bmlm NAMESPACE that you can extract a precompiled stanmodel from to pass to rstan::sampling.

Also, your two .stan files are almost identical except for a couple of lines, so they are good candidates to utilize the #include ... mechanism of rstan::stanc_builder, which is automatic for packages created by rstan::rstan.package.skeleton. You can put .stan files into inst/chunks that have all the common pieces and then put #include "piece.stan" in the appropriate place in your Stan programs and it will paste inst/chunks/piece.stan there. This way, there are fewer mistakes when you change something in one place and forget to change it in the other place(s). See https://github.com/stan-dev/rstanarm/blob/master/exec/polr.stan for one example of how to do this.

[mvuorre]

This is great, thanks so much for bringing these issues to my attention. I'll include these features in the next update.

[mvuorre]

These features are included in v1.1.0. Use

devtools::install_github("mvuorre/bmlm", args = "--preclean")

to install v1.1.0.