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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 0.0666 -0.324  0.00267 0.0666 0.0666
#>  2 1              2 0.371  -0.291  0.00636 0.371  0.371 
#>  3 1              3 0.746  -0.257  0.0140  0.746  0.746 
#>  4 1              4 0.630  -0.223  0.0286  0.630  0.630 
#>  5 1              5 0.407  -0.189  0.0540  0.407  0.407 
#>  6 1              6 0.0278 -0.156  0.0945  0.0278 0.0278
#>  7 1              7 0.200  -0.122  0.153   0.200  0.200 
#>  8 1              8 0.555  -0.0882 0.230   0.555  0.555 
#>  9 1              9 0.567  -0.0545 0.322   0.567  0.567 
#> 10 1             10 0.239  -0.0208 0.421   0.239  0.239 
#> # … with 40 more rows