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

Arguments

.n

The number of randomly generated points you want.

.shape

Shape parameter defaults to 0.

.scale

Scale parameter defaults to 1.

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

Author

Steven P. Sanderson II, MPH

Examples

tidy_weibull()
#> # A tibble: 50 × 7
#>    sim_number     x      y      dx      dy      p      q
#>    <fct>      <int>  <dbl>   <dbl>   <dbl>  <dbl>  <dbl>
#>  1 1              1 0.0463 -0.867  0.00100 0.0452 0.0463
#>  2 1              2 1.91   -0.740  0.00367 0.852  1.91  
#>  3 1              3 0.595  -0.612  0.0114  0.448  0.595 
#>  4 1              4 1.17   -0.484  0.0302  0.688  1.17  
#>  5 1              5 0.722  -0.357  0.0683  0.514  0.722 
#>  6 1              6 0.854  -0.229  0.133   0.574  0.854 
#>  7 1              7 0.908  -0.101  0.226   0.597  0.908 
#>  8 1              8 2.93    0.0265 0.337   0.946  2.93  
#>  9 1              9 0.200   0.154  0.447   0.181  0.200 
#> 10 1             10 2.83    0.282  0.535   0.941  2.83  
#> # ℹ 40 more rows