Construct an instance of S4 class stanmodel from a model 
  specified in Stan's modeling language. A stanmodel object 
  can then be used to draw samples from the model. The Stan program
  (the model expressed in the Stan modeling language) is first translated to
  C++ code and then the C++ code for the model plus other auxiliary 
  code is compiled into a dynamic shared object (DSO) and then loaded. 
  The loaded DSO for the model can be executed to draw samples, allowing
  inference to be performed for the model and data.
stan_model(file, model_name = "anon_model", 
             model_code = "", stanc_ret = NULL, 
             boost_lib = NULL, eigen_lib = NULL, 
             save_dso = TRUE, verbose = FALSE, 
             auto_write = rstan_options("auto_write"), 
             obfuscate_model_name = TRUE, 
             allow_undefined = FALSE, includes = NULL,
             isystem = c(if (!missing(file)) dirname(file), getwd()))A character string or a connection that R supports specifying the Stan model specification in Stan's modeling language.
A character string naming the model; defaults 
    to "anon_model". However, the model name will be derived from 
    file or model_code (if model_code is the name of a
    character string object) if model_name is not specified.
Either a character string containing the model 
    specification or the name of a character string object in the workspace.
    This is an alternative to specifying the model via the file
    or stanc_ret arguments.
A named list returned from a previous call to 
    the stanc function. The list can be used to specify the model  
    instead of using the file or model_code arguments.
The path to a version of the Boost C++ library to use instead of the one in the BH package.
The path to a version of the Eigen C++ library to use instead of the one in the RcppEigen package.
Logical, defaulting to TRUE, indicating 
    whether the  dynamic shared object (DSO) compiled from the C++ code for the 
    model will be saved or not. If TRUE, we can draw samples from
    the same model in another R session using the saved DSO (i.e., 
    without compiling the C++ code again).
Logical, defaulting to FALSE, indicating whether
    to report additional intermediate output to the console, 
    which might be helpful for debugging.
Logical, defaulting to the value of 
    rstan_options("auto_write"), indicating whether to write the
    object to the hard disk using saveRDS. Although this argument
    is FALSE by default, we recommend calling 
    rstan_options("auto_write" = TRUE) in order to avoid unnecessary 
    recompilations. If file is supplied and its dirname 
    is writable, then the object will be written to that same directory, 
    substituting a .rds extension for the .stan extension. 
    Otherwise, the object will be written to the tempdir.
A logical scalar that is TRUE by default and
    passed to stanc.
A logical scalar that is FALSE by default and
    passed to stanc.
If not NULL (the default), then a character vector of
    length one (possibly containing one or more "\n") of the form 
    '#include "/full/path/to/my_header.hpp"', which will be inserted
    into the C++ code in the model's namespace and can be used to provide definitions 
    of functions that are declared but not defined in file or
    model_code when allow_undefined = TRUE
A character vector naming a path to look for 
    file paths in file that are to be included within the Stan program
    named by file. See the Details section below.
An instance of S4 class '>stanmodel that can be
  passed to the sampling, optimizing, and 
  vb functions.
If a previously compiled stanmodel exists on the hard drive, its validity
  is checked and then returned without recompiling. The most common form of 
  invalidity seems to be Stan code that ends with a } rather than a blank
  line, which causes the hash checker to think that the current model is different
  than the one saved on the hard drive. To avoid reading previously 
  compiled stanmodels from the hard drive, supply the stanc_ret
  argument rather than the file or model_code arguments.
There are three ways to specify the model's code for stan_model:
parameter model_code: a character string containing the 
        Stan model specification,
parameter file: a file name (or a connection) from
       which to read the Stan model specification, or
parameter stanc_ret: a list returned by stanc
        to be reused.
The Stan Development Team Stan Modeling Language User's Guide and Reference Manual. http://mc-stan.org/.
'>stanmodel for details on the class.
sampling, optimizing, and vb, 
  which take a stanmodel object as input, for estimating the model 
  parameters.
More details on Stan, including the full user's guide and reference manual, can be found at http://mc-stan.org/.
# NOT RUN {
stancode <- 'data {real y_mean;} parameters {real y;} model {y ~ normal(y_mean,1);}'
mod <- stan_model(model_code = stancode, verbose = TRUE)
fit <- sampling(mod, data = list(y_mean = 0))
fit2 <- sampling(mod, data = list(y_mean = 5))
# }
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