The function plots a set of densities (per chain and coefficient) from the MCMC sample of an object of class "JointAI".

```
densplot(object, ...)
# S3 method for JointAI
densplot(object, start = NULL, end = NULL, thin = NULL,
subset = c(analysis_main = TRUE), outcome = NULL,
exclude_chains = NULL, vlines = NULL, nrow = NULL, ncol = NULL,
joined = FALSE, use_ggplot = FALSE, warn = TRUE, mess = TRUE, ...)
```

- object
object inheriting from class 'JointAI'

- ...
additional parameters passed to

`plot()`

- start
the first iteration of interest (see

`window.mcmc`

)- end
the last iteration of interest (see

`window.mcmc`

)- thin
thinning interval (integer; see

`window.mcmc`

). For example,`thin = 1`

(default) will keep the MCMC samples from all iterations;`thin = 5`

would only keep every 5th iteration.- subset
subset of parameters/variables/nodes (columns in the MCMC sample). Follows the same principle as the argument

`monitor_params`

in`*_imp`

.- outcome
optional; vector identifying a subset of sub-models included in the output, either by specifying their indices (using the order used in the list of model formulas), or their names (LHS of the respective model formula as character string)

- exclude_chains
optional vector of the index numbers of chains that should be excluded

- vlines
list, where each element is a named list of parameters that can be passed to

`graphics::abline()`

to create vertical lines. Each of the list elements needs to contain at least`v = <x location>`

where <x location> is a vector of the same length as the number of plots (see examples).- nrow
optional; number of rows in the plot layout; automatically chosen if unspecified

- ncol
optional; number of columns in the plot layout; automatically chosen if unspecified

- joined
logical; should the chains be combined before plotting?

- use_ggplot
logical; Should ggplot be used instead of the base graphics?

- warn
logical; should warnings be given? Default is

`TRUE`

.- mess
logical; should messages be given? Default is

`TRUE`

.

The vignette
Parameter Selection
contains some examples how to specify the argument `subset`

.

```
if (FALSE) {
# fit a JointAI object:
mod <- lm_imp(y ~ C1 + C2 + M1, data = wideDF, n.iter = 100)
# Example 1: basic densityplot
densplot(mod)
densplot(mod, exclude_chains = 2)
# Example 2: use vlines to mark zero
densplot(mod, col = c("darkred", "darkblue", "darkgreen"),
vlines = list(list(v = rep(0, nrow(summary(mod)$res$y$regcoef)),
col = grey(0.8))))
# Example 3: use vlines to visualize posterior mean and 2.5%/97.5% quantiles
res <- rbind(summary(mod)$res$y$regcoef[, c('Mean', '2.5%', '97.5%')],
summary(mod)$res$y$sigma[, c('Mean', '2.5%', '97.5%'),
drop = FALSE]
)
densplot(mod, vlines = list(list(v = res[, "Mean"], lty = 1, lwd = 2),
list(v = res[, "2.5%"], lty = 2),
list(v = res[, "97.5%"], lty = 2)))
# Example 4: ggplot version
densplot(mod, use_ggplot = TRUE)
# Example 5: change how the ggplot version looks
library(ggplot2)
densplot(mod, use_ggplot = TRUE) +
xlab("value") +
theme(legend.position = 'bottom') +
scale_color_brewer(palette = 'Dark2', name = 'chain')
}
```