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# Automatic Plot of Combined Multi Dist Data

Source: `R/autoplot-combined-dist.R`
`tidy_combined_autoplot.Rd`

This is an auto plotting function that will take in a `tidy_` distribution function and a few arguments, one being the plot type, which is a quoted string of one of the following:

- `density`

- `quantile`

- `probablity`

- `qq`

If the number of simulations exceeds 9 then the legend will not print. The plot subtitle is put together by the attributes of the table passed to the function.

## Usage

    tidy_combined_autoplot(
      .data,
      .plot_type = "density",
      .line_size = 0.5,
      .geom_point = FALSE,
      .point_size = 1,
      .geom_rug = FALSE,
      .geom_smooth = FALSE,
      .geom_jitter = FALSE,
      .interactive = FALSE
    )

## Arguments

.data

  The data passed in from a the function `tidy_multi_dist()`

.plot_type

  This is a quoted string like 'density'

.line_size

  The size param ggplot

.geom_point

  A Boolean value of TREU/FALSE, FALSE is the default. TRUE will return a plot with `ggplot2::ggeom_point()`

.point_size

  The point size param for ggplot

.geom_rug

  A Boolean value of TRUE/FALSE, FALSE is the default. TRUE will return the use of `ggplot2::geom_rug()`

.geom_smooth

  A Boolean value of TRUE/FALSE, FALSE is the default. TRUE will return the use of `ggplot2::geom_smooth()` The `aes` parameter of group is set to FALSE. This ensures a single smoothing band returned with SE also set to FALSE. Color is set to 'black' and `linetype` is 'dashed'.

.geom_jitter

  A Boolean value of TRUE/FALSE, FALSE is the default. TRUE will return the use of `ggplot2::geom_jitter()`

.interactive

  A Boolean value of TRUE/FALSE, FALSE is the default. TRUE will return an interactive `plotly` plot.

## Value

A ggplot or a plotly plot.

## Details

This function will spit out one of the following plots:

- `density`

- `quantile`

- `probability`

- `qq`

## See also

Other Autoplot: `bootstrap_stat_plot()`, `tidy_autoplot()`, `tidy_four_autoplot()`, `tidy_multi_dist_autoplot()`, `tidy_random_walk_autoplot()`

## Author

Steven P. Sanderson II, MPH

## Examples

    combined_tbl <- tidy_combine_distributions(
      tidy_normal(),
      tidy_gamma(),
      tidy_beta()
    )

    combined_tbl
    #> # A tibble: 150 × 8
    #>    sim_number     x       y    dx       dy      p       q dist_type
    #>    <fct>      <int>   <dbl> <dbl>    <dbl>  <dbl>   <dbl> <fct>
    #>  1 1              1 -1.36   -3.52 0.000368 0.0864 -1.36   Gaussian c(0, 1)
    #>  2 1              2 -1.20   -3.37 0.00102  0.116  -1.20   Gaussian c(0, 1)
    #>  3 1              3  0.804  -3.22 0.00254  0.789   0.804  Gaussian c(0, 1)
    #>  4 1              4  0.969  -3.06 0.00565  0.834   0.969  Gaussian c(0, 1)
    #>  5 1              5 -1.09   -2.91 0.0113   0.138  -1.09   Gaussian c(0, 1)
    #>  6 1              6 -1.38   -2.76 0.0203   0.0835 -1.38   Gaussian c(0, 1)
    #>  7 1              7 -0.672  -2.61 0.0331   0.251  -0.672  Gaussian c(0, 1)
    #>  8 1              8  0.371  -2.46 0.0498   0.645   0.371  Gaussian c(0, 1)
    #>  9 1              9  1.44   -2.30 0.0699   0.925   1.44   Gaussian c(0, 1)
    #> 10 1             10 -0.0394 -2.15 0.0931   0.484  -0.0394 Gaussian c(0, 1)
    #> # ℹ 140 more rows

    combined_tbl |>
      tidy_combined_autoplot()

    combined_tbl |>
      tidy_combined_autoplot(.plot_type = "qq")