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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  2.04  -3.37 0.000228 0.979   2.04  Gaussian c(0, 1)
#>  2 1              2  1.48  -3.23 0.000589 0.931   1.48  Gaussian c(0, 1)
#>  3 1              3 -0.435 -3.10 0.00137  0.332  -0.435 Gaussian c(0, 1)
#>  4 1              4 -0.986 -2.96 0.00290  0.162  -0.986 Gaussian c(0, 1)
#>  5 1              5 -1.36  -2.82 0.00555  0.0864 -1.36  Gaussian c(0, 1)
#>  6 1              6 -0.359 -2.69 0.00973  0.360  -0.359 Gaussian c(0, 1)
#>  7 1              7 -0.915 -2.55 0.0157   0.180  -0.915 Gaussian c(0, 1)
#>  8 1              8  0.774 -2.42 0.0237   0.781   0.774 Gaussian c(0, 1)
#>  9 1              9 -0.840 -2.28 0.0337   0.200  -0.840 Gaussian c(0, 1)
#> 10 1             10  0.348 -2.15 0.0461   0.636   0.348 Gaussian c(0, 1)
#> # … with 140 more rows

combined_tbl %>%
  tidy_combined_autoplot()


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