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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

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  0.00849 -3.28 0.000250 0.503  0.00849 Gaussian c(0, 1)
#>  2 1              2  0.481   -3.14 0.000670 0.685  0.481   Gaussian c(0, 1)
#>  3 1              3  2.22    -3.00 0.00162  0.987  2.22    Gaussian c(0, 1)
#>  4 1              4 -0.0905  -2.86 0.00355  0.464 -0.0905  Gaussian c(0, 1)
#>  5 1              5 -0.439   -2.72 0.00708  0.330 -0.439   Gaussian c(0, 1)
#>  6 1              6  2.01    -2.57 0.0129   0.978  2.01    Gaussian c(0, 1)
#>  7 1              7  1.39    -2.43 0.0218   0.917  1.39    Gaussian c(0, 1)
#>  8 1              8  0.444   -2.29 0.0340   0.672  0.444   Gaussian c(0, 1)
#>  9 1              9 -0.889   -2.15 0.0499   0.187 -0.889   Gaussian c(0, 1)
#> 10 1             10 -0.890   -2.01 0.0694   0.187 -0.890   Gaussian c(0, 1)
#> # ℹ 140 more rows

combined_tbl %>%
  tidy_combined_autoplot()


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