Skip to contents

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)

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.

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()

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 0.998  -0.367  0.00230 0.998  0.998 
#>  2 1              2 0.517  -0.332  0.00530 0.517  0.517 
#>  3 1              3 0.0161 -0.296  0.0113  0.0161 0.0161
#>  4 1              4 0.903  -0.260  0.0225  0.903  0.903 
#>  5 1              5 0.785  -0.224  0.0415  0.785  0.785 
#>  6 1              6 0.579  -0.189  0.0714  0.579  0.579 
#>  7 1              7 0.976  -0.153  0.114   0.976  0.976 
#>  8 1              8 0.752  -0.117  0.171   0.752  0.752 
#>  9 1              9 0.116  -0.0817 0.240   0.116  0.116 
#> 10 1             10 0.618  -0.0460 0.317   0.618  0.618 
#> # ℹ 40 more rows