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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

  • mcmc

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

  • mcmc

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")