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This function will generate n random points from an inverse gamma distribution with a user provided, .shape, .rate, .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_inverse_gamma(
  .n = 50,
  .shape = 1,
  .rate = 1,
  .scale = 1/.rate,
  .num_sims = 1
)

Arguments

.n

The number of randomly generated points you want.

.shape

Must be strictly positive.

.rate

An alternative way to specify the .scale

.scale

Must be strictly 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::rinvgamma(), and its underlying p, d, and q functions. For more information please see actuar::rinvgamma()

Author

Steven P. Sanderson II, MPH

Examples

tidy_inverse_gamma()
#> # A tibble: 50 × 7
#>    sim_number     x     y      dx       dy      p     q
#>    <fct>      <int> <dbl>   <dbl>    <dbl>  <dbl> <dbl>
#>  1 1              1 0.246 -2.92   0.000831 0.0171 0.246
#>  2 1              2 0.363 -2.18   0.00622  0.0634 0.363
#>  3 1              3 2.10  -1.43   0.0291   0.620  2.10 
#>  4 1              4 1.77  -0.685  0.0871   0.568  1.77 
#>  5 1              5 0.741  0.0602 0.170    0.260  0.741
#>  6 1              6 0.814  0.806  0.223    0.293  0.814
#>  7 1              7 1.19   1.55   0.204    0.430  1.19 
#>  8 1              8 0.928  2.30   0.141    0.341  0.928
#>  9 1              9 1.35   3.04   0.0829   0.476  1.35 
#> 10 1             10 0.358  3.79   0.0493   0.0611 0.358
#> # ℹ 40 more rows