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This function will generate n random points from a 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_pareto(
  .n = 50,
  .shape = 10,
  .scale = 0.1,
  .num_sims = 1,
  .return_tibble = TRUE
)

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.

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

Author

Steven P. Sanderson II, MPH

Examples

tidy_pareto()
#> # A tibble: 50 × 7
#>    sim_number     x        y        dx     dy      p        q
#>    <fct>      <int>    <dbl>     <dbl>  <dbl>  <dbl>    <dbl>
#>  1 1              1 0.00866  -0.0112    0.157 0.564  0.00866 
#>  2 1              2 0.0148   -0.00984   0.452 0.749  0.0148  
#>  3 1              3 0.000112 -0.00851   1.16  0.0111 0.000112
#>  4 1              4 0.00653  -0.00718   2.64  0.469  0.00653 
#>  5 1              5 0.00270  -0.00585   5.36  0.234  0.00270 
#>  6 1              6 0.0158   -0.00453   9.74  0.769  0.0158  
#>  7 1              7 0.00248  -0.00320  15.9   0.218  0.00248 
#>  8 1              8 0.0112   -0.00187  23.4   0.654  0.0112  
#>  9 1              9 0.0149   -0.000541 31.2   0.752  0.0149  
#> 10 1             10 0.0183    0.000787 38.0   0.814  0.0183  
#> # ℹ 40 more rows