This method allows to update an existing brmsfit object.
# S3 method for brmsfit
update(object, formula., newdata = NULL, recompile = NULL, ...)An object of class brmsfit.
Changes to the formula; for details see
update.formula and brmsformula.
Optional data.frame to update the model with new data.
Data-dependent default priors will not be updated automatically.
Logical, indicating whether the Stan model should
be recompiled. If NULL (the default), update tries
to figure out internally, if recompilation is necessary.
Setting it to FALSE will cause all Stan code changing
arguments to be ignored.
Other arguments passed to brm.
When updating a brmsfit created with the cmdstanr
backend in a different R session, a recompilation will be triggered
because by default, cmdstanr writes the model executable to a
temporary directory. To avoid that, set option
"cmdstanr_write_stan_file_dir" to a nontemporary path of your choice
before creating the original brmsfit (see section 'Examples' below).
if (FALSE) {
fit1 <- brm(time | cens(censored) ~ age * sex + disease + (1|patient),
data = kidney, family = gaussian("log"))
summary(fit1)
## remove effects of 'disease'
fit2 <- update(fit1, formula. = ~ . - disease)
summary(fit2)
## remove the group specific term of 'patient' and
## change the data (just take a subset in this example)
fit3 <- update(fit1, formula. = ~ . - (1|patient),
newdata = kidney[1:38, ])
summary(fit3)
## use another family and add population-level priors
fit4 <- update(fit1, family = weibull(), init = "0",
prior = set_prior("normal(0,5)"))
summary(fit4)
## to avoid a recompilation when updating a 'cmdstanr'-backend fit in a fresh
## R session, set option 'cmdstanr_write_stan_file_dir' before creating the
## initial 'brmsfit'
## CAUTION: the following code creates some files in the current working
## directory: two 'model_<hash>.stan' files, one 'model_<hash>(.exe)'
## executable, and one 'fit_cmdstanr_<some_number>.rds' file
set.seed(7)
fname <- paste0("fit_cmdstanr_", sample.int(.Machine$integer.max, 1))
options(cmdstanr_write_stan_file_dir = getwd())
fit_cmdstanr <- brm(rate ~ conc + state,
data = Puromycin,
backend = "cmdstanr",
file = fname)
# now restart the R session and run the following (after attaching 'brms')
set.seed(7)
fname <- paste0("fit_cmdstanr_", sample.int(.Machine$integer.max, 1))
fit_cmdstanr <- brm(rate ~ conc + state,
data = Puromycin,
backend = "cmdstanr",
file = fname)
upd_cmdstanr <- update(fit_cmdstanr,
formula. = rate ~ conc)
}