TidyDensity (version 1.5.0)

bootstrap_stat_plot: Bootstrap Stat Plot

Description

This function produces a plot of a cumulative statistic function applied to the bootstrap variable from tidy_bootstrap() or after bootstrap_unnest_tbl() has been applied to it.

Usage

bootstrap_stat_plot(
  .data,
  .value,
  .stat = "cmean",
  .show_groups = FALSE,
  .show_ci_labels = TRUE,
  .interactive = FALSE
)

Value

A plot either ggplot2 or plotly.

Arguments

.data

The data that comes from either tidy_bootstrap() or after bootstrap_unnest_tbl() is applied to it.

.value

The value column that the calculations are being applied to.

.stat

The cumulative statistic function being applied to the .value column. It must be quoted. The default is "cmean".

.show_groups

The default is FALSE, set to TRUE to get output of all simulations of the bootstrap data.

.show_ci_labels

The default is TRUE, this will show the last value of the upper and lower quantile.

.interactive

The default is FALSE, set to TRUE to get a plotly plot object back.

Author

Steven P. Sanderson II, MPH

Details

This function will take in data from either tidy_bootstrap() directly or after apply bootstrap_unnest_tbl() to its output. There are several different cumulative functions that can be applied to the data.The accepted values are:

• "cmean" - Cumulative Mean

• "chmean" - Cumulative Harmonic Mean

• "cgmean" - Cumulative Geometric Mean

• "csum" = Cumulative Sum

• "cmedian" = Cumulative Median

• "cmax" = Cumulative Max

• "cmin" = Cumulative Min

• "cprod" = Cumulative Product

• "csd" = Cumulative Standard Deviation

• "cvar" = Cumulative Variance

• "cskewness" = Cumulative Skewness

• "ckurtosis" = Cumulative Kurtotsis

See Also

Other Bootstrap: bootstrap_density_augment(), bootstrap_p_augment(), bootstrap_p_vec(), bootstrap_q_augment(), bootstrap_q_vec(), bootstrap_unnest_tbl(), tidy_bootstrap()

Other Autoplot: tidy_autoplot(), tidy_combined_autoplot(), tidy_four_autoplot(), tidy_multi_dist_autoplot(), tidy_random_walk_autoplot()

Examples

x <- mtcars$mpg

tidy_bootstrap(x) |>
  bootstrap_stat_plot(y, "cmean")

tidy_bootstrap(x, .num_sims = 10) |>
  bootstrap_stat_plot(y,
    .stat = "chmean", .show_groups = TRUE,
    .show_ci_label = FALSE
  )