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This function will generate n random points from an inverse exponential distribution with a user provided, .rate or .scale 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_inverse_exponential(.n = 50, .rate = 1, .scale = 1/.rate, .num_sims = 1)

Arguments

.n

The number of randomly generated points you want.

.rate

An alternative way to specify the .scale

.scale

Must be strictly positive.

.num_sims

The number of randomly generated simulations you want.

Value

A tibble of randomly generated data.

Details

This function uses the underlying actuar::rinvexp(), and its underlying p, d, and q functions. For more information please see actuar::rinvexp()

Author

Steven P. Sanderson II, MPH

Examples

tidy_inverse_exponential()
#> # A tibble: 50 × 7
#>    sim_number     x     y     dx       dy       p     q
#>    <fct>      <int> <dbl>  <dbl>    <dbl>   <dbl> <dbl>
#>  1 1              1 3.60  -2.03  0.000608 0.757   3.60 
#>  2 1              2 0.203 -1.12  0.0150   0.00720 0.203
#>  3 1              3 2.17  -0.220 0.0986   0.630   2.17 
#>  4 1              4 1.38   0.683 0.221    0.484   1.38 
#>  5 1              5 1.47   1.59  0.233    0.508   1.47 
#>  6 1              6 3.48   2.49  0.164    0.750   3.48 
#>  7 1              7 1.10   3.39  0.140    0.402   1.10 
#>  8 1              8 3.58   4.30  0.0994   0.756   3.58 
#>  9 1              9 3.33   5.20  0.0424   0.740   3.33 
#> 10 1             10 3.44   6.11  0.0318   0.748   3.44 
#> # ℹ 40 more rows