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This function will generate n random points from an inverse pareto distribution with a user provided, .shape, .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_pareto(.n = 50, .shape = 1, .scale = 1, .num_sims = 1)

Arguments

.n

The number of randomly generated points you want.

.shape

Must be positive.

.scale

Must be 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::rinvpareto(), and its underlying p, d, and q functions. For more information please see actuar::rinvpareto()

Author

Steven P. Sanderson II, MPH

Examples

tidy_inverse_pareto()
#> # A tibble: 50 × 7
#>    sim_number     x       y     dx      dy      p       q
#>    <fct>      <int>   <dbl>  <dbl>   <dbl>  <dbl>   <dbl>
#>  1 1              1  0.513  -2.11  0.00109 0.339   0.513 
#>  2 1              2  0.268  -1.18  0.0311  0.211   0.268 
#>  3 1              3 10.4    -0.251 0.191   0.912  10.4   
#>  4 1              4  0.0180  0.679 0.303   0.0177  0.0180
#>  5 1              5 41.3     1.61  0.193   0.976  41.3   
#>  6 1              6  0.616   2.54  0.0952  0.381   0.616 
#>  7 1              7  0.0414  3.47  0.0403  0.0398  0.0414
#>  8 1              8  2.18    4.40  0.0188  0.685   2.18  
#>  9 1              9  1.44    5.33  0.0323  0.590   1.44  
#> 10 1             10  0.674   6.26  0.0302  0.403   0.674 
#> # ℹ 40 more rows