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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 0.0347   -0.0105     0.180 0.949  0.0347  
#>  2 1              2 0.0222   -0.00838    0.952 0.865  0.0222  
#>  3 1              3 0.00302  -0.00630    3.72  0.257  0.00302 
#>  4 1              4 0.000731 -0.00421   10.8   0.0702 0.000731
#>  5 1              5 0.00427  -0.00212   23.8   0.342  0.00427 
#>  6 1              6 0.0495   -0.0000278 39.8   0.982  0.0495  
#>  7 1              7 0.00690   0.00206   51.9   0.487  0.00690 
#>  8 1              8 0.0179    0.00415   54.6   0.808  0.0179  
#>  9 1              9 0.0100    0.00624   48.9   0.616  0.0100  
#> 10 1             10 0.0232    0.00833   40.2   0.876  0.0232  
#> # … with 40 more rows