R Markdown supports a variety of languages through the use of knitr
language engines. One such engine is the stan
engine, which
allows users to write Stan programs directly in their R Markdown
documents by setting the language of the chunk to stan
.
Behind the scenes, the engine relies on RStan to compile the model
code into an in-memory stanmodel
, which is assigned to a
variable with the name given by the output.var
chunk
option. For example:
CmdStanR provides a replacement engine, which can be registered as follows:
library(cmdstanr)
check_cmdstan_toolchain(fix = TRUE, quiet = TRUE)
register_knitr_engine()
By default, this overrides knitr’s built-in stan
engine
so that all stan
chunks are processed with CmdStanR, not
RStan. Of course, this also means that the variable specified by
output.var
will no longer be a stanmodel
object, but instead a CmdStanModel
object, so the code
above would look like this:
// This stan chunk results in a CmdStanModel object called "ex1"
parameters {
array[2] real y;
}
model {
y[1] ~ normal(0, 1);
y[2] ~ double_exponential(0, 2);
}
ex1$print()
#> // This stan chunk results in a CmdStanModel object called "ex1"
#> parameters {
#> array[2] real y;
#> }
#> model {
#> y[1] ~ normal(0, 1);
#> y[2] ~ double_exponential(0, 2);
#> }
fit <- ex1$sample(
refresh = 0,
seed = 42L
)
#> Running MCMC with 4 sequential chains...
#>
#> Chain 1 finished in 0.0 seconds.
#> Chain 2 finished in 0.0 seconds.
#> Chain 3 finished in 0.0 seconds.
#> Chain 4 finished in 0.0 seconds.
#>
#> All 4 chains finished successfully.
#> Mean chain execution time: 0.0 seconds.
#> Total execution time: 0.7 seconds.
print(fit)
#> variable mean median sd mad q5 q95 rhat ess_bulk ess_tail
#> lp__ -1.50 -1.17 1.24 0.96 -3.94 -0.18 1.00 1304 1536
#> y[1] -0.01 -0.01 0.99 0.99 -1.67 1.60 1.00 1993 2262
#> y[2] -0.07 -0.04 2.90 2.05 -4.79 4.54 1.00 2050 1420
Use cache=TRUE
chunk option to avoid re-compiling the
Stan model code every time the R Markdown is knit/rendered.
You can find the Stan model file and the compiled executable in the document’s cache directory.
While the default behavior is to override the built-in
stan
engine because the assumption is that the user is
probably not using both RStan and CmdStanR in the same document or
project, the option to use both exists. When registering CmdStanR’s
knitr engine, set override = FALSE
to register the engine
as a cmdstan
engine:
register_knitr_engine(override = FALSE)
This will cause stan
chunks to be processed by knitr’s
built-in, RStan-based engine and only use CmdStanR’s knitr engine for
cmdstan
chunks:
When running chunks interactively in RStudio (e.g. when using R
Notebooks), it has been observed that the built-in, RStan-based
engine is used for stan
chunks even when CmdStanR’s engine
has been registered in the session as the engine for stan
.
As a workaround, when running chunks interactively, it is
recommended to use the override = FALSE
option and change
stan
chunks to be cmdstan
chunks.
Do not worry: if the template you use supports syntax highlighting
for the Stan language, that syntax highlighting will be applied to
cmdstan
chunks when the document is knit/rendered.