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# Tidy Randomly Generated Uniform Distribution Tibble

Source: `R/random-tidy-uniform.R`
`tidy_uniform.Rd`

This function will generate `n` random points from a uniform distribution with a user provided, `.min` and `.max` values, and number of random simulations to be produced. The function returns a tibble with the simulation number column the x column which corresponds to the n randomly generated points, the `d_`, `p_` and `q_` data points as well.

The data is returned un-grouped.

The columns that are output are:

- `sim_number` The current simulation number.

- `x` The current value of `n` for the current simulation.

- `y` The randomly generated data point.

- `dx` The `x` value from the `stats::density()` function.

- `dy` The `y` value from the `stats::density()` function.

- `p` The values from the resulting p_ function of the distribution family.

- `q` The values from the resulting q_ function of the distribution family.

## Usage

    tidy_uniform(.n = 50, .min = 0, .max = 1, .num_sims = 1, .return_tibble = TRUE)

## Arguments

.n

  The number of randomly generated points you want.

.min

  A lower limit of the distribution.

.max

  An upper limit of the distribution

.num_sims

  The number of randomly generated simulations you want.

.return_tibble

  A logical value indicating whether to return the result as a tibble. Default is TRUE.

## Value

A tibble of randomly generated data.

## Details

This function uses the underlying `stats::runif()`, and its underlying `p`, `d`, and `q` functions. For more information please see `stats::runif()`

## See also

https://www.itl.nist.gov/div898/handbook/eda/section3/eda3662.htm

Other Continuous Distribution: `tidy_beta()`, `tidy_burr()`, `tidy_cauchy()`, `tidy_chisquare()`, `tidy_exponential()`, `tidy_f()`, `tidy_gamma()`, `tidy_generalized_beta()`, `tidy_generalized_pareto()`, `tidy_geometric()`, `tidy_inverse_burr()`, `tidy_inverse_exponential()`, `tidy_inverse_gamma()`, `tidy_inverse_normal()`, `tidy_inverse_pareto()`, `tidy_inverse_weibull()`, `tidy_logistic()`, `tidy_lognormal()`, `tidy_normal()`, `tidy_paralogistic()`, `tidy_pareto()`, `tidy_pareto1()`, `tidy_t()`, `tidy_triangular()`, `tidy_weibull()`, `tidy_zero_truncated_geometric()`

Other Uniform: `util_uniform_param_estimate()`, `util_uniform_stats_tbl()`

## Author

Steven P. Sanderson II, MPH

## Examples

    tidy_uniform()
    #> # A tibble: 50 × 7
    #>    sim_number     x      y      dx      dy      p      q
    #>    <fct>      <int>  <dbl>   <dbl>   <dbl>  <dbl>  <dbl>
    #>  1 1              1 0.0624 -0.378  0.00158 0.0624 0.0624
    #>  2 1              2 0.725  -0.342  0.00387 0.725  0.725
    #>  3 1              3 0.719  -0.306  0.00881 0.719  0.719
    #>  4 1              4 0.841  -0.270  0.0186  0.841  0.841
    #>  5 1              5 0.375  -0.235  0.0367  0.375  0.375
    #>  6 1              6 0.668  -0.199  0.0674  0.668  0.668
    #>  7 1              7 0.821  -0.163  0.115   0.821  0.821
    #>  8 1              8 0.283  -0.127  0.184   0.283  0.283
    #>  9 1              9 0.993  -0.0916 0.275   0.993  0.993
    #> 10 1             10 0.271  -0.0559 0.385   0.271  0.271
    #> # ℹ 40 more rows