Takes an input vector of numeric data and produces a bootstrapped nested tibble by simulation number.
Arguments
- .x
The vector of data being passed to the function. Must be a numeric vector.
- .num_sims
The default is 2000, can be set to anything desired. A warning will pass to the console if the value is less than 2000.
- .proportion
How much of the original data do you want to pass through to the sampling function. The default is 0.80 (80%)
- .distribution_type
This can either be 'continuous' or 'discrete'
Details
This function will take in a numeric input vector and produce a tibble
of bootstrapped values in a list. The table that is output will have two columns:
sim_number and bootstrap_samples
The sim_number corresponds to how many times you want the data to be resampled,
and the bootstrap_samples column contains a list of the boostrapped resampled
data.
See also
Other Bootstrap:
bootstrap_density_augment(),
bootstrap_p_augment(),
bootstrap_p_vec(),
bootstrap_q_augment(),
bootstrap_q_vec(),
bootstrap_stat_plot(),
bootstrap_unnest_tbl()
Examples
x <- mtcars$mpg
tidy_bootstrap(x)
#> # A tibble: 2,000 × 2
#> sim_number bootstrap_samples
#> <fct> <list>
#> 1 1 <dbl [25]>
#> 2 2 <dbl [25]>
#> 3 3 <dbl [25]>
#> 4 4 <dbl [25]>
#> 5 5 <dbl [25]>
#> 6 6 <dbl [25]>
#> 7 7 <dbl [25]>
#> 8 8 <dbl [25]>
#> 9 9 <dbl [25]>
#> 10 10 <dbl [25]>
#> # ℹ 1,990 more rows