`bru()`

uses `INLA::inla()`

to fit models. The latter estimates the posterior densities of
all random effects in the model. This function serves to access and plot the posterior
densities in a convenient way.

Requires the `ggplot2`

package.

## Usage

```
# S3 method for bru
plot(x, ...)
```

## Arguments

- x
a fitted

`bru()`

model.- ...
A character naming the effect to plot, e.g. "Intercept". For random effects, adding

`index = ...`

plots the density for a single component of the latent model.

## Examples

```
if (FALSE) {
if (require("ggplot2", quietly = TRUE)) {
# Generate some data and fit a simple model
input.df <- data.frame(x = cos(1:10))
input.df <- within(input.df, y <- 5 + 2 * cos(1:10) + rnorm(10, mean = 0, sd = 0.1))
fit <- bru(y ~ x, family = "gaussian", data = input.df)
summary(fit)
# Plot the posterior of the model's x-effect
plot(fit, "x")
}
}
```