Create a bootstrapper function useful for repeated reproducible bootstrapping

Create a bootstrapper function useful for repeated reproducible bootstrapping

bootstrapper(times, group = NULL, seed = NULL, key = ".draw",
  row = ".row", id = ".id", original_id = ".original_id",
  copies = ".copies")

Arguments

times	Number of independent bootstrap draws to perform.
group	An optional expression setting up the grouping to use for bootstrapping. If not provided, any grouping present in the original dataset will be used.
seed	Random seed to use.
key	Name (as character) of the column that will hold an integer running from 1 to times indicating the bootstrap replicate.
row	Name (as character) of the column that will hold an integer counting rows in the final bootstrapped dataset. Useful for animations with gganimate.
id	Name (as character) of the column that will hold an integer running from 1 to n for each bootstrap, where n is the number of observations in each group.
original_id	Name (as character) of the column that indicates the row from which the bootstrapped row originates.
copies	Name (as character) of the column that reports how often a specific original row has been oversampled.

See also

sampler()

Examples

bs <- bootstrapper(3)
bs(data.frame(letter = letters[1:4]))
#> # A tibble: 12 x 6
#> # Groups:   .draw [3]
#>    .draw   .id .original_id letter .copies  .row
#>    <int> <int>        <int> <fct>    <dbl> <int>
#>  1     1     1            3 c            2     1
#>  2     1     2            3 c            2     2
#>  3     1     3            1 a            1     3
#>  4     1     4            2 b            1     4
#>  5     2     1            1 a            4     5
#>  6     2     2            1 a            4     6
#>  7     2     3            1 a            4     7
#>  8     2     4            1 a            4     8
#>  9     3     1            3 c            2     9
#> 10     3     2            2 b            2    10
#> 11     3     3            2 b            2    11
#> 12     3     4            3 c            2    12

library(ggplot2)
library(dplyr)
#> 
#> Attaching package: ‘dplyr’
#> The following object is masked from ‘package:testthat’:
#> 
#>     matches
#> The following objects are masked from ‘package:stats’:
#> 
#>     filter, lag
#> The following objects are masked from ‘package:base’:
#> 
#>     intersect, setdiff, setequal, union
ggplot(iris, aes(Sepal.Length, Sepal.Width)) +
  geom_point() +
  geom_smooth(data = bootstrapper(5, Species), aes(group = .draw), se = FALSE) +
  facet_wrap(~Species)
#> `geom_smooth()` using method = 'loess' and formula 'y ~ x'

# it is important to set grouping correctly for bootstrapping
set.seed(1234)

df <- data.frame(
  type = c(rep("A", 100), rep("B", 10), rep("C", 3)),
  y = rnorm(113)
)

# incorrect: bootstrapping ungrouped dataset leads to missing category C
ggplot(df, aes(type, y)) +
  geom_pointrange(data = bootstrapper(6, seed = 562), stat = "summary") +
  facet_wrap(~.draw)
#> No summary function supplied, defaulting to `mean_se()
#> No summary function supplied, defaulting to `mean_se()
#> No summary function supplied, defaulting to `mean_se()
#> No summary function supplied, defaulting to `mean_se()
#> No summary function supplied, defaulting to `mean_se()
#> No summary function supplied, defaulting to `mean_se()
#> Warning: Removed 1 rows containing missing values (geom_pointrange).

# correct: bootstrapping within groups
ggplot(df, aes(type, y)) +
  geom_pointrange(data = bootstrapper(6, type, seed = 562), stat = "summary") +
  facet_wrap(~.draw)
#> No summary function supplied, defaulting to `mean_se()
#> No summary function supplied, defaulting to `mean_se()
#> No summary function supplied, defaulting to `mean_se()
#> No summary function supplied, defaulting to `mean_se()
#> No summary function supplied, defaulting to `mean_se()
#> No summary function supplied, defaulting to `mean_se()

# also correct: use grouped data frame
ggplot(group_by(df, type), aes(type, y)) +
  geom_pointrange(data = bootstrapper(6, seed = 562), stat = "summary") +
  facet_wrap(~.draw)
#> No summary function supplied, defaulting to `mean_se()
#> No summary function supplied, defaulting to `mean_se()
#> No summary function supplied, defaulting to `mean_se()
#> No summary function supplied, defaulting to `mean_se()
#> No summary function supplied, defaulting to `mean_se()
#> No summary function supplied, defaulting to `mean_se()

# NOT RUN {
library(gganimate)

set.seed(69527)
x <- rnorm(15)
data <- data.frame(
  x,
  y = x + 0.5*rnorm(15)
)

bs <- bootstrapper(9)

p <- ggplot(data, aes(x, y)) +
  geom_point(shape = 21, size = 6, fill = "white") +
  geom_text(label = "0", hjust = 0.5, vjust = 0.5, size = 10/.pt) +
  geom_point(data = bs, aes(group = .row), shape = 21, size = 6, fill = "blue") +
  geom_text(
    data = bs, aes(label = .copies, group = .row),
    hjust = 0.5, vjust = 0.5, size = 10/.pt, color = "white"
  ) +
  geom_smooth(data = bs, method = "lm", se = FALSE) +
  ggtitle("Bootstrap demonstration") +
  theme_bw()

p + facet_wrap(~.draw)
p + transition_states(.draw, 1, 1) +
  enter_fade() + exit_fade()
# }