`autoplot`

can produce a series of plot to summarise results of simulation studies. See `vignette("C-plotting", package = "rsimsum")`

for further details.

## Usage

```
# S3 method for simsum
autoplot(
object,
type = "forest",
stats = "nsim",
target = NULL,
fitted = TRUE,
scales = "fixed",
top = TRUE,
density.legend = TRUE,
zoom = 1,
zip_ci_colours = "yellow",
...
)
```

## Arguments

- object
An object of class

`simsum`

.- type
The type of the plot to be produced. Possible choices are:

`forest`

,`lolly`

,`zip`

,`est`

,`se`

,`est_ba`

,`se_ba`

,`est_ridge`

,`se_ridge`

,`est_density`

,`se_density`

,`est_hex`

,`se_hex`

,`heat`

,`nlp`

, with`forest`

being the default.- stats
Summary statistic to plot, defaults to

`nsim`

(the number of replications with non-missing point estimates/SEs). See`summary.simsum()`

for further details on supported summary statistics.- target
Target of summary statistic, e.g. 0 for

`bias`

. Defaults to`NULL`

, in which case target will be inferred.- fitted
Superimpose a fitted regression line, useful when

`type`

= (`est`

,`se`

,`est_ba`

,`se_ba`

,`est_density`

,`se_density`

,`est_hex`

,`se_hex`

). Defaults to`TRUE`

.- scales
Should scales be fixed (

`fixed`

, the default), free (`free`

), or free in one dimension (`free_x`

,`free_y`

)?- top
Should the legend for a nested loop plot be on the top side of the plot? Defaults to

`TRUE`

.- density.legend
Should the legend for density and hexbin plots be included? Defaults to

`TRUE`

.- zoom
A numeric value between 0 and 1 signalling that a zip plot should

*zoom*on the top x% of the plot (to ease interpretation). Defaults to 1, where the whole zip plot is displayed.- zip_ci_colours
A string with (1) a hex code to use for plotting coverage probability and its Monte Carlo confidence intervals (the default, with value

`zip_ci_colours = "yellow"`

), (2) a string vector of two hex codes denoting optimal coverage (first element) and over/under coverage (second element) or (3) a vector of three hex codes denoting optimal coverage (first), undercoverage (second), and overcoverage (third).- ...
Not used.

## Examples

```
data("MIsim", package = "rsimsum")
s <- rsimsum::simsum(
data = MIsim, estvarname = "b", true = 0.5, se = "se",
methodvar = "method", x = TRUE
)
#> 'ref' method was not specified, CC set as the reference
library(ggplot2)
autoplot(s)
autoplot(s, type = "lolly")
autoplot(s, type = "est_hex")
#> `geom_smooth()` using formula = 'y ~ x'
autoplot(s, type = "zip", zoom = 0.5)
# Nested loop plot:
data("nlp", package = "rsimsum")
s1 <- rsimsum::simsum(
data = nlp, estvarname = "b", true = 0, se = "se",
methodvar = "model", by = c("baseline", "ss", "esigma")
)
#> 'ref' method was not specified, 1 set as the reference
autoplot(s1, stats = "bias", type = "nlp")
```