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This function will generate n random points from a single parameter pareto distribution with a user provided, .shape, .min, 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_pareto1(.n = 50, .shape = 1, .min = 1, .num_sims = 1)

Arguments

.n

The number of randomly generated points you want.

.shape

Must be positive.

.min

The lower bound of the support of the distribution.

.num_sims

The number of randomly generated simulations you want.

Value

A tibble of randomly generated data.

Details

This function uses the underlying actuar::rpareto1(), and its underlying p, d, and q functions. For more information please see actuar::rpareto1()

Author

Steven P. Sanderson II, MPH

Examples

tidy_pareto1()
#> # A tibble: 50 × 7
#>    sim_number     x     y     dx      dy     p     q
#>    <fct>      <int> <dbl>  <dbl>   <dbl> <dbl> <dbl>
#>  1 1              1  2.27 -0.883 0.00148 0.560  2.27
#>  2 1              2  1.41 -0.162 0.0292  0.289  1.41
#>  3 1              3  5.39  0.559 0.177   0.815  5.39
#>  4 1              4  5.38  1.28  0.354   0.814  5.38
#>  5 1              5  2.26  2.00  0.281   0.558  2.26
#>  6 1              6  1.42  2.72  0.153   0.298  1.42
#>  7 1              7  1.31  3.44  0.0887  0.234  1.31
#>  8 1              8  1.35  4.16  0.0615  0.262  1.35
#>  9 1              9  2.43  4.88  0.0664  0.588  2.43
#> 10 1             10  1.85  5.60  0.0588  0.458  1.85
#> # ℹ 40 more rows