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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 0.279  -0.341  0.00299 0.279  0.279 
#>  2 1              2 0.393  -0.307  0.00729 0.393  0.393 
#>  3 1              3 0.845  -0.273  0.0164  0.845  0.845 
#>  4 1              4 0.237  -0.239  0.0339  0.237  0.237 
#>  5 1              5 0.494  -0.205  0.0647  0.494  0.494 
#>  6 1              6 0.357  -0.171  0.114   0.357  0.357 
#>  7 1              7 0.860  -0.137  0.186   0.860  0.860 
#>  8 1              8 0.892  -0.104  0.283   0.892  0.892 
#>  9 1              9 0.0792 -0.0696 0.400   0.0792 0.0792
#> 10 1             10 0.170  -0.0357 0.530   0.170  0.170 
#> # ℹ 40 more rows