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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  3.07 -0.620 0.000851     0.675   3.07
#>  2 1              2  1.72  0.761 0.159        0.417   1.72
#>  3 1              3  1.70  2.14  0.283        0.411   1.70
#>  4 1              4  6.35  3.52  0.116        0.842   6.35
#>  5 1              5  1.84  4.90  0.0377       0.456   1.84
#>  6 1              6  1.04  6.28  0.0183       0.0351  1.04
#>  7 1              7  1.62  7.66  0.0301       0.384   1.62
#>  8 1              8  4.32  9.05  0.0145       0.769   4.32
#>  9 1              9  1.29 10.4   0.000247     0.226   1.29
#> 10 1             10  3.00 11.8   0.0000000111 0.667   3.00
#> # ℹ 40 more rows