Calculate the log-probability, the gradient w.r.t. each input, and the Hessian for a given vector of unconstrained parameters

The $hessian() method provides access to the Stan model's log_prob, its derivative, and its Hessian.

Usage

hessian(unconstrained_variables, jacobian = TRUE)

Arguments

unconstrained_variables

(numeric) A vector of unconstrained parameters.

jacobian

(logical) Whether to include the log-density adjustments from constraining or unconstraining variables.

Value

A named list with elements log_prob, grad_log_prob, and hessian.

See also

log_prob(), grad_log_prob(), constrain_variables(), unconstrain_variables(), unconstrain_draws()

Examples

# \dontrun{
fit_mcmc <- cmdstanr_example("logistic", method = "sample", force_recompile = TRUE)
# fit_mcmc$init_model_methods()
# fit_mcmc$hessian(unconstrained_variables = c(0.5, 1.2, 1.1, 2.2))
# }