| expose_stan_functions {rstan} | R Documentation |
Expose user-defined Stan functions to R for testing and simulation
Description
The Stan modeling language allows users to define their own functions in a
functions block at the top of a Stan program. The
expose_stan_functions utility function uses
sourceCpp to export those user-defined functions
to the specified environment for testing inside R or for doing posterior
predictive simulations in R rather than in the generated
quantities block of a Stan program.
Usage
expose_stan_functions(stanmodel, includes = NULL,
show_compiler_warnings = FALSE, ...)
get_rng(seed = 0L)
get_stream()
Arguments
stanmodel |
A |
includes |
If not |
show_compiler_warnings |
Logical scalar defaulting to |
seed |
An integer vector of length one indicating the state of Stan's pseudo-random number generator |
... |
Further arguments passed to |
Details
The expose_stan_functions function requires as much compliance with
the C++14 standard as is implemented in the RTools toolchain for Windows.
On Windows, you will likely need to specify CXX14 = g++ -std=c++1y
in the file whose path is normalizePath("~/.R/Makevars") in
order for expose_stan_functions to work. Outside of Windows, the
necessary compiler flags are set programatically, which is likely to suffice.
There are a few special types of user-defined Stan functions for which some additional details are relevant:
(P)RNG functions
If a user-defined Stan function ends in _rng, then it can
use the Boost pseudo-random number generator used by Stan. When exposing
such functions to R, base_rng__ and pstream__ arguments will
be added to the formals. The base_rng__ argument should
be passed the result of a call to get_rng (perhaps specifying its
seed argument for reproducibility) and the pstream__ should
be passed the result of a call to get_stream, which can be used to
see the result of print and reject calls in the user-defined
Stan functions. These arguments default to get_stream() and
get_rng() respectively.
LP functions
If a user-defined Stan function ends in _lp, then it can
modify the log-probability used by Stan to evaluate Metropolis
proposals or as an objective function for optimization. When exposing
such functions to R, a lp__ argument will be added to the
formals. This lp__ argument defaults to zero, but a
double precision scalar may be passed to this argument when the
function is called from R. Such a user-defined Stan function can terminate
with return target(); or can execute print(target()); to verify that
the calculation is correct.
Value
The names of the new functions in env are returned invisibly.
See Also
sourceCpp and the section in the Stan User Manual on
user-defined functions
Examples
## Not run:
model_code <-
'
functions {
real standard_normal_rng() {
return normal_rng(0,1);
}
}
'
expose_stan_functions(stanc(model_code = model_code))
standard_normal_rng()
PRNG <- get_rng(seed = 3)
o <- get_stream()
standard_normal_rng(PRNG, o)
## End(Not run)