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This function will generate n random points from a exponential distribution with a user provided, .rate, 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_exponential(.n = 50, .rate = 1, .num_sims = 1, .return_tibble = TRUE)

Arguments

.n

The number of randomly generated points you want.

.rate

A vector of rates

.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::rexp(), and its underlying p, d, and q functions. For more information please see stats::rexp()

Author

Steven P. Sanderson II, MPH

Examples

tidy_exponential()
#> # A tibble: 50 × 7
#>    sim_number     x     y      dx       dy     p     q
#>    <fct>      <int> <dbl>   <dbl>    <dbl> <dbl> <dbl>
#>  1 1              1 1.29  -0.796  0.000736 0.724 1.29 
#>  2 1              2 0.996 -0.669  0.00315  0.631 0.996
#>  3 1              3 0.503 -0.543  0.0111   0.395 0.503
#>  4 1              4 0.853 -0.416  0.0322   0.574 0.853
#>  5 1              5 0.690 -0.290  0.0773   0.499 0.690
#>  6 1              6 2.19  -0.163  0.155    0.888 2.19 
#>  7 1              7 0.601 -0.0369 0.262    0.452 0.601
#>  8 1              8 1.52   0.0896 0.380    0.781 1.52 
#>  9 1              9 0.986  0.216  0.480    0.627 0.986
#> 10 1             10 0.999  0.343  0.544    0.632 0.999
#> # ℹ 40 more rows