Fit models for use in examples
cmdstanr_example(
example = c("logistic", "schools", "schools_ncp"),
method = c("sample", "optimize", "laplace", "variational", "pathfinder", "diagnose"),
...,
quiet = TRUE,
force_recompile = getOption("cmdstanr_force_recompile", default = FALSE)
)
print_example_program(example = c("logistic", "schools", "schools_ncp"))
(string) The name of the example. The currently available examples are
"logistic"
: logistic regression with intercept and 3 predictors.
"schools"
: the so-called "eight schools" model, a hierarchical
meta-analysis. Fitting this model will result in warnings about
divergences.
"schools_ncp"
: non-centered parameterization of the "eight schools"
model that fixes the problem with divergences.
To print the Stan code for a given example
use
print_example_program(example)
.
(string) Which fitting method should be used? The default is
the "sample"
method (MCMC).
Arguments passed to the chosen method
. See the help pages for
the individual methods for details.
(logical) If TRUE
(the default) then fitting the model is
wrapped in utils::capture.output()
.
Passed to the $compile() method.
The fitted model object returned by the selected method
.
if (FALSE) { # \dontrun{
print_example_program("logistic")
fit_logistic_mcmc <- cmdstanr_example("logistic", chains = 2)
fit_logistic_mcmc$summary()
fit_logistic_optim <- cmdstanr_example("logistic", method = "optimize")
fit_logistic_optim$summary()
fit_logistic_vb <- cmdstanr_example("logistic", method = "variational")
fit_logistic_vb$summary()
print_example_program("schools")
fit_schools_mcmc <- cmdstanr_example("schools")
fit_schools_mcmc$summary()
print_example_program("schools_ncp")
fit_schools_ncp_mcmc <- cmdstanr_example("schools_ncp")
fit_schools_ncp_mcmc$summary()
# optimization fails for hierarchical model
cmdstanr_example("schools", "optimize", quiet = FALSE)
} # }