log_prob and grad_log_prob functionslog_prob and grad_log_prob functions
on the unconstrained space of model parameters. Sometimes we
need to convert the values of parameters from their support defined
in the parameters block (which might be constrained, and for simplicity,
we call it the constrained space) to the unconstrained space and vice versa.
The constrain_pars and unconstrain_pars functions are used
for this purpose.
"log_prob"(object, upars, adjust_transform = TRUE, gradient = FALSE) "grad_log_prob"(object, upars, adjust_transform = TRUE) "get_num_upars"(object) "constrain_pars"(object, upars) "unconstrain_pars"(object, pars)stanfit.log_prob returns a value (up to an additive constant) the log posterior.
If gradient is TRUE, the gradients are also returned as an
attribute with name gradient.grad_log_prob returns a vector of the gradients. Additionally, the vector
has an attribute named log_prob being the value the same as log_prob
is called for the input parameters.get_num_upars returns the number of parameters on the unconstrained space.constrain_pars returns a list and unconstrain_pars returns a vector.
lp__) for the model represented by a stanfit object. Compute the gradients
for log_prob as well as the log posterior. The latter is returned as
an attribute. Get the number
of unconstrained parameters. Convert values
of the parameter from unconstrained space (given as a vector) to their
constrained space (returned as a named list).
Contrary to
constrained, conert values of the parameters from constrained
to unconstrained space. log_prob and grad_log_prob functions
accept an adjust_transform argument.
stanfit