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This function will generate n random points from a weibull distribution with a user provided, .shape, .scale, .rate, 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_weibull(
  .n = 50,
  .shape = 1,
  .rate = 1,
  .scale = 1/.rate,
  .num_sims = 1,
  .return_tibble = TRUE
)

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.

.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::rinvweibull(), and its underlying p, d, and q functions. For more information please see actuar::rinvweibull()

Author

Steven P. Sanderson II, MPH

Examples

tidy_inverse_weibull()
#> # A tibble: 50 × 7
#>    sim_number     x     y     dx       dy      p     q
#>    <fct>      <int> <dbl>  <dbl>    <dbl>  <dbl> <dbl>
#>  1 1              1 0.663 -2.52  0.000601 0.221  0.663
#>  2 1              2 2.58  -1.15  0.0272   0.679  2.58 
#>  3 1              3 0.563  0.217 0.181    0.169  0.563
#>  4 1              4 5.31   1.59  0.222    0.828  5.31 
#>  5 1              5 3.98   2.96  0.0981   0.778  3.98 
#>  6 1              6 0.419  4.33  0.0480   0.0918 0.419
#>  7 1              7 4.91   5.70  0.0261   0.816  4.91 
#>  8 1              8 3.28   7.07  0.0236   0.737  3.28 
#>  9 1              9 0.963  8.44  0.0229   0.354  0.963
#> 10 1             10 3.67   9.82  0.00787  0.762  3.67 
#> # ℹ 40 more rows