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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)

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.

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 1.63  -1.03   0.00253 0.805 1.63 
#>  2 1              2 0.113 -0.890  0.00844 0.107 0.113
#>  3 1              3 0.519 -0.748  0.0242  0.405 0.519
#>  4 1              4 0.321 -0.607  0.0596  0.275 0.321
#>  5 1              5 4.86  -0.465  0.126   0.992 4.86 
#>  6 1              6 0.190 -0.323  0.229   0.173 0.190
#>  7 1              7 0.136 -0.181  0.361   0.127 0.136
#>  8 1              8 0.317 -0.0397 0.493   0.271 0.317
#>  9 1              9 1.22   0.102  0.588   0.705 1.22 
#> 10 1             10 2.14   0.244  0.618   0.883 2.14 
#> # ℹ 40 more rows