Nothing
Code
sizes4
Output
# A tibble: 5 x 5
analysis assessment n p id
<int> <int> <int> <int> <chr>
1 49669 18552 50000 3 Bootstrap1
2 49943 17429 50000 3 Bootstrap2
3 50133 16350 50000 3 Bootstrap3
4 50314 18071 50000 3 Bootstrap4
5 50253 17830 50000 3 Bootstrap5
Code
group_bootstraps(warpbreaks, tension)
Condition
Warning in `group_bootstraps()`:
Some assessment sets contained zero rows.
i Consider using a non-grouped resampling method.
Output
# Group bootstrap sampling
# A tibble: 25 x 2
splits id
<list> <chr>
1 <split [54/18]> Bootstrap01
2 <split [54/36]> Bootstrap02
3 <split [54/18]> Bootstrap03
4 <split [54/18]> Bootstrap04
5 <split [54/36]> Bootstrap05
6 <split [54/18]> Bootstrap06
7 <split [54/18]> Bootstrap07
8 <split [54/18]> Bootstrap08
9 <split [54/18]> Bootstrap09
10 <split [54/18]> Bootstrap10
# i 15 more rows
Code
bootstraps(mtcars[2, ])
Condition
Warning in `bootstraps()`:
Some assessment sets contained zero rows.
Output
# Bootstrap sampling
# A tibble: 25 x 2
splits id
<list> <chr>
1 <split [1/0]> Bootstrap01
2 <split [1/0]> Bootstrap02
3 <split [1/0]> Bootstrap03
4 <split [1/0]> Bootstrap04
5 <split [1/0]> Bootstrap05
6 <split [1/0]> Bootstrap06
7 <split [1/0]> Bootstrap07
8 <split [1/0]> Bootstrap08
9 <split [1/0]> Bootstrap09
10 <split [1/0]> Bootstrap10
# i 15 more rows
Code
set.seed(11)
bootstraps(warpbreaks)
Output
# Bootstrap sampling
# A tibble: 25 x 2
splits id
<list> <chr>
1 <split [54/20]> Bootstrap01
2 <split [54/22]> Bootstrap02
3 <split [54/17]> Bootstrap03
4 <split [54/22]> Bootstrap04
5 <split [54/17]> Bootstrap05
6 <split [54/19]> Bootstrap06
7 <split [54/18]> Bootstrap07
8 <split [54/17]> Bootstrap08
9 <split [54/23]> Bootstrap09
10 <split [54/22]> Bootstrap10
# i 15 more rows
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