Create plots of from predictNMB simulations.

## Usage

```
# S3 method for class 'predictNMBsim'
autoplot(
object,
what = c("nmb", "inb", "cutpoints", "qalys", "costs"),
inb_ref_col = NA,
conf.level = 0.95,
methods_order = NULL,
n_bins = 40,
label_wrap_width = 12,
fill_cols = c("grey50", "#ADD8E6"),
median_line_size = 2,
median_line_alpha = 0.5,
median_line_col = "black",
rename_vector,
...
)
```

## Arguments

- object
A

`predictNMBsim`

object.- what
What to summarise: one of "nmb", "inb", "cutpoints", "qalys" or "costs". Defaults to "nmb".

- inb_ref_col
Which cutpoint method to use as the reference strategy when calculating the incremental net monetary benefit. See

`do_nmb_sim`

for more information.- conf.level
The confidence level of the interval. Defaults to 0.95 (coloured area of distribution represents 95% CIs).

- methods_order
The order (left to right) to display the cutpoint methods.

- n_bins
The number of bins used when constructing histograms. Defaults to 40.

- label_wrap_width
The number of characters in facet labels at which the label is wrapped. Default is 12.

- fill_cols
Vector containing the colours used for fill aesthetic of histograms. The first colour represents the area outside of the confidence region, second colour shows the confidence region. Defaults to

`c("grey50", "#ADD8E6")`

.- median_line_size
Size of line used to represent the median of distribution. Defaults to 2.

- median_line_alpha
Alpha (transparency) for line used to represent the median of distribution. Defaults to 0.5.

- median_line_col
Colour of line used to represent the median of distribution. Defaults to

`"black"`

.- rename_vector
A named vector for renaming the methods in the summary. The values of the vector are the default names and the names given are the desired names in the output.

- ...
Additional (unused) arguments.

## Details

This plot method works with `predictNMBsim`

objects that are created
using `do_nmb_sim()`

. Can be used to visualise distributions from
simulations for different cutpoint methods.

## Examples

```
# \donttest{
get_nmb <- function() c("TP" = -3, "TN" = 0, "FP" = -1, "FN" = -4)
sim_obj <- do_nmb_sim(
sample_size = 200, n_sims = 50, n_valid = 10000, sim_auc = 0.7,
event_rate = 0.1, fx_nmb_training = get_nmb, fx_nmb_evaluation = get_nmb,
cutpoint_methods = c("all", "none", "youden", "value_optimising")
)
autoplot(
sim_obj,
rename_vector = c(
"Value- Optimising" = "value_optimising",
"Treat- None" = "none",
"Treat- All" = "all",
"Youden Index" = "youden"
)
) + theme_sim()
# }
```