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
)
```

- parameters
List of parameters, see

`set_parameters`

- n_distributions
The target number of distributions to return.

- seed
An integer to use as the seed for random number generation. Set this in scripts to ensure reproducibility.

- return_tibble
Should a tibble, rather than a list, be returned? Requires the

`tibble`

-package, ignored if that package is not available.- return_failures
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:

- outcome
success or failure - character

- distribution
The distribution that was found (if success) / that had the closest variance (if failure) - numeric

- mean
The exact mean of the distribution - numeric

- sd
The SD of the distribution that was found (success) / that came closest (failure) - numeric

- iterations
The number of iterations required to achieve the specified SD - numeric - the first time this distribution was found

```
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]> 2.2 1.32 3
#> 2 2 success <dbl [20]> 2.25 1.25 1
#> 3 3 success <dbl [20]> 2.2 1.32 6
#> 4 4 success <dbl [20]> 2.25 1.33 1
#> 5 5 success <dbl [20]> 2.25 1.33 2
```