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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)

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::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 0.00420   -0.0115     0.143 0.337   0.00420  
#>  2 1              2 0.0136    -0.00984    0.515 0.720   0.0136   
#>  3 1              3 0.0109    -0.00819    1.56  0.644   0.0109   
#>  4 1              4 0.0107    -0.00654    3.98  0.639   0.0107   
#>  5 1              5 0.0148    -0.00489    8.60  0.749   0.0148   
#>  6 1              6 0.00113   -0.00324   15.8   0.106   0.00113  
#>  7 1              7 0.0000660 -0.00159   24.9   0.00658 0.0000660
#>  8 1              8 0.0107     0.0000577 34.0   0.637   0.0107   
#>  9 1              9 0.0235     0.00171   41.1   0.878   0.0235   
#> 10 1             10 0.0164     0.00336   45.0   0.781   0.0164   
#> # ℹ 40 more rows