- formula
An object of class `formula`

,
`brmsformula`

, or `mvbrmsformula`

(or one that can
be coerced to that classes): A symbolic description of the model to be
fitted. The details of model specification are explained in
`brmsformula`

.

- data
An object of class `data.frame`

(or one that can be coerced
to that class) containing data of all variables used in the model.

- family
A description of the response distribution and link function to
be used in the model. This can be a family function, a call to a family
function or a character string naming the family. Every family function has
a `link`

argument allowing to specify the link function to be applied
on the response variable. If not specified, default links are used. For
details of supported families see `brmsfamily`

. By default, a
linear `gaussian`

model is applied. In multivariate models,
`family`

might also be a list of families.

- autocor
(Deprecated) An optional `cor_brms`

object
describing the correlation structure within the response variable (i.e.,
the 'autocorrelation'). See the documentation of `cor_brms`

for
a description of the available correlation structures. Defaults to
`NULL`

, corresponding to no correlations. In multivariate models,
`autocor`

might also be a list of autocorrelation structures.
It is now recommend to specify autocorrelation terms directly
within `formula`

. See `brmsformula`

for more details.

- data2
A named `list`

of objects containing data, which
cannot be passed via argument `data`

. Required for some objects
used in autocorrelation structures to specify dependency structures
as well as for within-group covariance matrices.

- knots
Optional list containing user specified knot values to be used
for basis construction of smoothing terms. See
`gamm`

for more details.

- drop_unused_levels
Should unused factors levels in the data be
dropped? Defaults to `TRUE`

.

- sparse
(Deprecated) Logical; indicates whether the population-level
design matrices should be treated as sparse (defaults to `FALSE`

). For
design matrices with many zeros, this can considerably reduce required
memory. Sampling speed is currently not improved or even slightly
decreased. It is now recommended to use the `sparse`

argument of
`brmsformula`

and related functions.

- ...
Other arguments for internal usage only.