Add function bootstrap_unnest_tbl()

[spsanderson]

Function:

bootstrap_unnest_tbl <- function(.data){
  
  # Checks ----
  atb <- attributes(.data)
  distribution_family_type <- atb$dist_type
  
  if (!atb$tibble_type == "tidy_bootstrap"){
    rlang::abort(
      message = "You must provide the output from the tidy_bootstrap() function.",
      use_cli_format = TRUE
    )
  }
  
  # Data ----
  df <- tidyr::unnest(.data, bootstrap_samples) %>%
    purrr::set_names("sim_number", "y")
  
  # Return ----
  attr(df, ".num_sims") <- atb$.num_sims
  attr(df, "distribution_family_tpe") <- distribution_family_type
  attr(df, "tibble_type") <- "tidy_bootstrap"
  attr(df, "dist_with_params") <- "Empirical"
  
  return(df)
  
}

Example:

> tb <- tidy_bootstrap(.x = mtcars$mpg)
> bootstrap_unnest_tbl(tb)
# A tibble: 50,000 x 2
   sim_number     y
   <fct>      <dbl>
 1 1           22.8
 2 1           17.3
 3 1           22.8
 4 1           19.2
 5 1           14.3
 6 1           24.4
 7 1           18.7
 8 1           21  
 9 1           10.4
10 1           21.5
# ... with 49,990 more rows
> 
> bootstrap_unnest_tbl(tb) %>%
+   tidy_distribution_summary_tbl(sim_number)
# A tibble: 2,000 x 11
   sim_number mean_val median_val std_val min_val max_val skewness kurtosis range   iqr
   <fct>         <dbl>      <dbl>   <dbl>   <dbl>   <dbl>    <dbl>    <dbl> <dbl> <dbl>
 1 1              19.4       19.2    5.19    10.4    30.4    0.251     2.87  20    7.8 
 2 2              19.9       19.2    5.23    10.4    33.9    0.487     3.69  23.5  3.7 
 3 3              19.3       18.7    5.17    10.4    33.9    0.761     4.14  23.5  4.10
 4 4              20.0       19.7    5.92    10.4    33.9    0.701     3.33  23.5  6.3 
 5 5              18.4       18.7    4.65    10.4    32.4    0.762     4.62  22    5.5 
 6 6              19.2       17.8    6.27    10.4    33.9    0.951     3.62  23.5  6   
 7 7              22.2       19.7    6.48    14.7    33.9    0.682     1.93  19.2 13.1 
 8 8              20.2       19.2    6.83    10.4    33.9    0.556     2.50  23.5  7.6 
 9 9              19.5       17.3    7.13    10.4    33.9    0.747     2.36  23.5  6.3 
10 10             19.8       18.1    5.72    10.4    32.4    0.999     3.56  22    5.9 
# ... with 1,990 more rows, and 1 more variable: variance <dbl>
> 
> bootstrap_unnest_tbl(tb) %>%
+   tidy_distribution_summary_tbl()
# A tibble: 1 x 10
  mean_val median_val std_val min_val max_val skewness kurtosis range   iqr variance
     <dbl>      <dbl>   <dbl>   <dbl>   <dbl>    <dbl>    <dbl> <dbl> <dbl>    <dbl>
1     20.1       19.2    5.92    10.4    33.9    0.641     2.81  23.5   7.3     35.0
> 
> mean(mtcars$mpg)
[1] 20.09062