update.bmmfit: Update a bmm model

In bmm: Easy and Accessible Bayesian Measurement Models Using 'brms'

Update a bmm model

Description

Update an existing bmm mode. This function calls brms::update.brmsfit(), but it applies the necessary bmm postprocessing to the model object before and after the update.

Usage

## S3 method for class 'bmmfit'
update(object, formula., newdata = NULL, recompile = NULL, ...)

Arguments

object	An object of class bmmfit
formula.	A bmmformula(). If missing, the original formula is used. Currently you have to specify a full bmmformula
newdata	An optional data frame containing the variables in the model
recompile	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.
...	Further arguments passed to brms::update.brmsfit()

Details

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 bmmfit.

For more information and examples, see brms::update.brmsfit()

Value

An updated bmmfit object refit to the new data and/or formula

Examples

# generate artificial data from the Signal Discrimination Model
# generate artificial data from the Signal Discrimination Model
dat <- data.frame(y = rsdm(2000))

# define formula
ff <- bmf(c ~ 1, kappa ~ 1)

# fit the model
fit <- bmm(formula = ff,
           data = dat,
           model = sdm(resp_error = "y"),
           cores = 4,
           backend = 'cmdstanr')

# update the model
fit <- update(fit, newdata = data.frame(y = rsdm(2000, kappa = 5)))

bmm documentation built on May 29, 2024, 11:52 a.m.