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This function will generate n random points from a gamma 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_gamma(.n = 50, .shape = 1, .scale = 0.3, .num_sims = 1)

Arguments

.n

The number of randomly generated points you want.

.shape

This is strictly 0 to infinity.

.scale

The standard deviation of the randomly generated data. This is strictly from 0 to infinity.

.num_sims

The number of randomly generated simulations you want.

Value

A tibble of randomly generated data.

Details

This function uses the underlying stats::rgamma(), and its underlying p, d, and q functions. For more information please see stats::rgamma()

Author

Steven P. Sanderson II, MPH

Examples

tidy_gamma()
#> # A tibble: 50 × 7
#>    sim_number     x      y       dx      dy     p      q
#>    <fct>      <int>  <dbl>    <dbl>   <dbl> <dbl>  <dbl>
#>  1 1              1 0.464  -0.288   0.00550 0.787 0.464 
#>  2 1              2 0.885  -0.256   0.0144  0.948 0.885 
#>  3 1              3 0.141  -0.225   0.0344  0.374 0.141 
#>  4 1              4 0.268  -0.194   0.0743  0.591 0.268 
#>  5 1              5 0.109  -0.163   0.146   0.304 0.109 
#>  6 1              6 0.369  -0.132   0.262   0.707 0.369 
#>  7 1              7 0.0815 -0.101   0.429   0.238 0.0815
#>  8 1              8 0.388  -0.0702  0.644   0.726 0.388 
#>  9 1              9 0.820  -0.0392  0.892   0.935 0.820 
#> 10 1             10 0.422  -0.00813 1.14    0.755 0.422 
#> # ℹ 40 more rows