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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,
  .return_tibble = TRUE
)

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.

.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::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  1.47 -2.65   0.000922 0.321   1.47
#>  2 1              2  1.05 -1.32   0.0156   0.0485  1.05
#>  3 1              3  8.45  0.0124 0.0886   0.882   8.45
#>  4 1              4  9.99  1.35   0.179    0.900   9.99
#>  5 1              5 45.3   2.68   0.149    0.978  45.3 
#>  6 1              6  1.45  4.01   0.0776   0.312   1.45
#>  7 1              7  2.51  5.34   0.0499   0.602   2.51
#>  8 1              8  1.51  6.68   0.0305   0.338   1.51
#>  9 1              9  7.32  8.01   0.0200   0.863   7.32
#> 10 1             10  2.12  9.34   0.0200   0.529   2.12
#> # ℹ 40 more rows