suppress all output from RStan

Requested by Avraham Adler on stan-users:

Firstly, as a medium-term lurker but first-time poster, I would like to thank the entire Stan development team for the creation and maintenance of Stan.

I am using Stan as part of a paper I am trying to write, and I am struggling with trying to suppress diagnostic messages. For example, when I have used JAGS, R2jags, and knitr, once I set echo, messages, and warnings to FALSE, I can have the model run every time I knit the paper, and only have the results I want displayed through \Sexpr{}. Using Stan, I am having much more of a problem. I have searched the group and have found the following threads:

• Suppressing Warning Messages
• silent stan?
• RStan print() - Trivial request

I have verbose set to FALSE and refresh set to -1. I have used suppressMessages/Warnings as suggested in the thread (1), and that does not seem to do anything more than setting messages and warnings settings in the knitr chunk. I have wrapped my stan() call in sink() calls, as discussed in thread (2) as such:

<<'Bayes_Stan', eval=TRUE, echo=FALSE, message=FALSE, warning=FALSE, cache=0>>=
sink(file = "a", type = c("output", "message"))
library(rstan)
LN_S <- suppressMessages(suppressWarnings(stan(file = 'Bayes.stan', data = BayesData, pars = c('mu', 'sigma', 'LR_post', 'ASL_post', 'dev'), iter = 300000, warmup = 50000, thin = 25, chains = 5, seed = 12, refresh = -1, verbose = FALSE)))

[snip extractions and assignments]

LNPlus_S <- suppressMessages(suppressWarnings(stan(file = 'BayesPlus.stan', data = BayesDataPlus, pars = c('Pars', 'LR_post', 'ASL_post', 'dev'), iter = 300000, warmup = 50000, thin = 25, chains = 5, seed = 12, refresh = -1, verbose = FALSE)))

[snip extractions and assignments]
sink()
@

Regardless, my knitted output looks like:

…Therefore, the model was rebuilt in Stan (Stan Development Team, 2014a)—a Bayesian modeling language whose samplers are non-Gibbs.
##
## TRANSLATING MODEL 'Bayes' FROM Stan CODE TO C++ CODE NOW.
## COMPILING THE C++ CODE FOR MODEL 'Bayes' NOW.
## cygwin warning:
## MS-DOS style path detected: C:/R/RCurrent/R-30~1.2/etc/x64/Makeconf
## Preferred POSIX equivalent is: /cygdrive/c/R/RCurrent/R-30~1.2/etc/x64/Makeconf
## CYGWIN environment variable option "nodosfilewarning" turns off this warning.
## Consult the user's guide for more details about POSIX paths:
## http://cygwin.com/cygwin-ug-net/using.html#using-pathnames
## C:/R/RCurrent/R-3.0.2/library/rstan/include//stansrc/stan/agrad/rev/var_stack.hpp:49:17: warning: 'void stan::agrad::free_memory()' defined but not used [-Wunused-function]
## C:/R/RCurrent/R-3.0.2/library/rstan/include//stansrc/stan/agrad/rev/chainable.hpp:87:17: warning: 'void stan::agrad::set_zero_all_adjoints()' defined but not used [-Wunused-function]
##
## TRANSLATING MODEL 'BayesPlus' FROM Stan CODE TO C++ CODE NOW.
## COMPILING THE C++ CODE FOR MODEL 'BayesPlus' NOW.
## cygwin warning:
## MS-DOS style path detected: C:/R/RCurrent/R-30~1.2/etc/x64/Makeconf
## Preferred POSIX equivalent is: /cygdrive/c/R/RCurrent/R-30~1.2/etc/x64/Makeconf
## CYGWIN environment variable option "nodosfilewarning" turns off this warning.
## Consult the user's guide for more details about POSIX paths:
## http://cygwin.com/cygwin-ug-net/using.html#using-pathnames
## C:/R/RCurrent/R-3.0.2/library/rstan/include//stansrc/stan/agrad/rev/var_stack.hpp:49:17: warning: 'void stan::agrad::free_memory()' defined but not used [-Wunused-function]
## C:/R/RCurrent/R-3.0.2/library/rstan/include//stansrc/stan/agrad/rev/chainable.hpp:87:17: warning: 'void stan::agrad::set_zero_all_adjoints()' defined but not used [-Wunused-function]
## Error in function stan::prob::lognormal_log(N4stan5agrad3varE): Scale parameter is -0.34910650273000776:0, but must be > 0!Rejecting proposed initial value with zero density.
## Error in function stan::prob::lognormal_log(N4stan5agrad3varE): Scale parameter is -1.6172265406146098:0, but must be > 0!Rejecting proposed initial value with zero density.
## Error in function stan::prob::lognormal_log(N4stan5agrad3varE): Scale parameter is -1.2449912107872052:0, but must be > 0!Rejecting proposed initial value with zero density.
## Error in function stan::prob::lognormal_log(N4stan5agrad3varE): Scale parameter is -1.0263658781850085:0, but must be > 0!Rejecting proposed initial value with zero density.
## Error in function stan::prob::lognormal_log(N4stan5agrad3varE): Scale parameter is -1.7036664255500364:0, but must be > 0!Rejecting proposed initial value with zero density.
## Error in function stan::prob::lognormal_log(N4stan5agrad3varE): Scale parameter is -1.7912999475616009:0, but must be > 0!Rejecting proposed initial value with zero density.
## Error in function stan::prob::lognormal_log(N4stan5agrad3varE): Scale parameter is -0.67853001987262718:0, but must be > 0!Rejecting proposed initial value with zero density.
## Error in function stan::prob::lognormal_log(N4stan5agrad3varE): Scale parameter is -0.56723437122169695:0, but must be > 0!Rejecting proposed initial value with zero density.
## Error in function stan::prob::lognormal_log(N4stan5agrad3varE): Scale parameter is -1.9622578028376079:0, but must be > 0!Rejecting proposed initial value with zero density.
## Error in function stan::prob::lognormal_log(N4stan5agrad3varE): Scale parameter is -1.9058489407892381:0, but must be > 0!Rejecting proposed initial value with zero density.
The No-U-Turn-Sampler behind Stan is much more robust to highly autocorrelated parameters…

While I can always knit the Rnw, edit the resulting tex file to remove these lines, and re-texify that file, I would appreciate knowing if there is any way to prevent the need for such post-processing.