Plot estimates from models

```
plot_models(
model_list,
samples,
inference,
parameter,
plot_type = "base",
prior = FALSE,
conditional = FALSE,
order = NULL,
transformation = NULL,
transformation_arguments = NULL,
transformation_settings = FALSE,
par_name = NULL,
formula_prefix = TRUE,
...
)
```

- model_list
list of models, each of which contains marginal likelihood estimated with bridge sampling

`marglik`

and prior model odds`prior_weights`

- samples
samples from a posterior distribution for a parameter generated by mix_posteriors.

- inference
object created by ensemble_inference function

- parameter
parameter name to be plotted. Does not support PET-PEESE and weightfunction.

- plot_type
whether to use a base plot

`"base"`

or ggplot2`"ggplot"`

for plotting.- prior
whether prior distribution should be added to the figure

- conditional
whether conditional models should be displayed

- order
list specifying ordering of the models. The first element describes whether the ordering should be

`"increasing"`

or`"decreasing"`

and the second element describes whether the ordering should be based`"model"`

order,`"estimate"`

size, posterior`"probability"`

, or the inclusion`"BF"`

.- transformation
transformation to be applied to the prior distribution. Either a character specifying one of the prepared transformations:

- lin
linear transformation in form of

`a + b*x`

- tanh
also known as Fisher's z transformation

- exp
exponential transformation

, or a list containing the transformation function

`fun`

, inverse transformation function`inv`

, and the Jacobian of the transformation`jac`

. See examples for details.- transformation_arguments
a list with named arguments for the

`transformation`

- transformation_settings
boolean indicating whether the settings the

`x_seq`

or`x_range`

was specified on the transformed support- par_name
a type of parameter for which the prior is specified. Only relevant if the prior corresponds to a mu parameter that needs to be transformed.

- formula_prefix
whether the

`formula_parameters`

names should be kept. Defaults to`TRUE`

.- ...
additional arguments. E.g.:

`"show_updating"`

whether Bayes factors and change from prior to posterior odds should be shown on the secondary y-axis

`"show_estimates"`

whether posterior estimates and 95% CI should be shown on the secondary y-axis

`"y_axis2"`

whether the secondary y-axis should be shown

`plot_models`

returns either `NULL`

or
an object of class 'ggplot' if plot_type is `plot_type = "ggplot"`

.

Plots prior and posterior estimates of the same parameter across multiple models (prior distributions with orthonormal/meandif contrast are always plotted as differences from the grand mean).