`update.RoBTT`

can be used to

change the prior odds of fitted models by specifying a vector

`prior_weights`

of the same length as the fitted models,refitting models that failed to converge with updated settings of control parameters,

or changing the convergence criteria and recalculating the ensemble results by specifying new

`control`

argument and setting`refit_failed == FALSE`

.

```
# S3 method for RoBTT
update(
object,
refit_failed = TRUE,
prior_weights = NULL,
chains = NULL,
iter = NULL,
warmup = NULL,
thin = NULL,
parallel = NULL,
control = NULL,
convergence_checks = NULL,
save = "all",
seed = NULL,
silent = TRUE,
...
)
```

- object
a fitted RoBTT object

- refit_failed
whether failed models should be refitted. Relevant only

`prior_weights`

are not supplied. Defaults to`TRUE`

.- prior_weights
either a single value specifying prior model weight of a newly specified model using priors argument, or a vector of the same length as already fitted models to update their prior weights.

- chains
a number of chains of the MCMC algorithm.

- iter
a number of sampling iterations of the MCMC algorithm. Defaults to

`10000`

, with a minimum of`4000`

.- warmup
a number of warmup iterations of the MCMC algorithm. Defaults to

`5000`

.- thin
a thinning of the chains of the MCMC algorithm. Defaults to

`1`

.- parallel
whether the individual models should be fitted in parallel. Defaults to

`FALSE`

. The implementation is not completely stable and might cause a connection error.- control
allows to pass control settings with the

`set_control()`

function. See`?set_control`

for options and default settings.- convergence_checks
automatic convergence checks to assess the fitted models, passed with

`set_convergence_checks()`

function. See`?set_convergence_checks`

for options and default settings.- save
whether all models posterior distributions should be kept after obtaining a model-averaged result. Defaults to

`"all"`

which does not remove anything. Set to`"min"`

to significantly reduce the size of final object, however, some model diagnostics and further manipulation with the object will not be possible.- seed
a seed to be set before model fitting, marginal likelihood computation, and posterior mixing for reproducibility of results. Defaults to

`NULL`

- no seed is set.- silent
whether all print messages regarding the fitting process should be suppressed. Defaults to

`TRUE`

. Note that`parallel = TRUE`

also suppresses all messages.- ...
additional arguments.

`RoBTT`

returns an object of class 'RoBTT'.

See `RoBTT()`

for more details.