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 0.701   -0.369  0.00141 0.701   0.701  
#>  2 1              2 0.00275 -0.334  0.00333 0.00275 0.00275
#>  3 1              3 0.239   -0.299  0.00730 0.239   0.239  
#>  4 1              4 0.602   -0.264  0.0149  0.602   0.602  
#>  5 1              5 0.904   -0.228  0.0282  0.904   0.904  
#>  6 1              6 0.222   -0.193  0.0500  0.222   0.222  
#>  7 1              7 0.187   -0.158  0.0827  0.187   0.187  
#>  8 1              8 0.865   -0.123  0.129   0.865   0.865  
#>  9 1              9 0.0330  -0.0882 0.189   0.0330  0.0330 
#> 10 1             10 0.608   -0.0532 0.262   0.608   0.608  
#> # ℹ 40 more rows