Creates a set of traceplots from the MCMC sample of an object of class 'JointAI'.

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

- object
object inheriting from class 'JointAI'

- ...
Arguments passed on to

`graphics::matplot`

`lty`

vector of line types, widths, and end styles. The first element is for the first column, the second element for the second column, etc., even if lines are not plotted for all columns. Line types will be used cyclically until all plots are drawn.

`lwd`

vector of line types, widths, and end styles. The first element is for the first column, the second element for the second column, etc., even if lines are not plotted for all columns. Line types will be used cyclically until all plots are drawn.

`lend`

vector of line types, widths, and end styles. The first element is for the first column, the second element for the second column, etc., even if lines are not plotted for all columns. Line types will be used cyclically until all plots are drawn.

`col`

vector of colors. Colors are used cyclically.

`cex`

vector of character expansion sizes, used cyclically. This works as a multiple of

`par("cex")`

.`NULL`

is equivalent to`1.0`

.`bg`

vector of background (fill) colors for the open plot symbols given by

`pch = 21:25`

as in`points`

. The default`NA`

corresponds to the one of the underlying function`plot.xy`

.`add`

logical. If

`TRUE`

, plots are added to current one, using`points`

and`lines`

.`verbose`

logical. If

`TRUE`

, write one line of what is done.

- 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

- 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

- 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`

.

`summary.JointAI`

,
`*_imp`

,
`densplot`

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

.

```
# fit a JointAI model
mod <- lm_imp(y ~ C1 + C2 + M1, data = wideDF, n.iter = 100)
# Example 1: simple traceplot
traceplot(mod)
# Example 2: ggplot version of traceplot
traceplot(mod, use_ggplot = TRUE)
# Example 5: changing how the ggplot version looks (using ggplot syntax)
library(ggplot2)
traceplot(mod, use_ggplot = TRUE) +
theme(legend.position = 'bottom') +
xlab('iteration') +
ylab('value') +
scale_color_discrete(name = 'chain')
```