This function aims to find several possible distribution that would give rise to
the observed sample parameters. For that, you need to pass a list of parameters,
created with set_parameters
find_possible_distributions(
parameters,
n_distributions = 10,
seed = NULL,
return_tibble = TRUE,
return_failures = FALSE
)List of parameters, see set_parameters
The target number of distributions to return.
An integer to use as the seed for random number generation. Set this in scripts to ensure reproducibility. Explicit seeds leave the caller's random number generator state unchanged.
Should a tibble, rather than a list, be returned? Requires the tibble-package, ignored if that package is not available.
Should distributions that failed to produce the desired SD be returned? Defaults to false
A tibble or list (depending on the return_tibble argument) with:
success or failure - character
The distribution that was found (if success) / whose SD came closest to the target during the search (if failure) - numeric
The exact mean of the distribution - numeric
The SD of the distribution that was found (success) / that came closest (failure) - numeric
The number of SD adjustments attempted on the first search that found this distribution. Zero if its initial candidate succeeded; on failure, the total number attempted.
A successful search supplies one compatible reconstruction. Search failure does not prove impossibility, and the frequencies with which reconstructions are found do not estimate probabilities for the original data. Rounding ties are accepted in either direction.
sprite_parameters <- set_parameters(mean = 2.2, sd = 1.3, n_obs = 20,
min_val = 1, max_val = 5)
find_possible_distributions(sprite_parameters, 5, seed = 1234)
#> # A tibble: 5 × 6
#> id outcome distribution mean sd iterations
#> <int> <chr> <list> <dbl> <dbl> <dbl>
#> 1 1 success <dbl [20]> 2.25 1.25 0
#> 2 2 success <dbl [20]> 2.25 1.25 1
#> 3 3 success <dbl [20]> 2.15 1.31 4
#> 4 4 success <dbl [20]> 2.25 1.33 0
#> 5 5 success <dbl [20]> 2.25 1.33 1