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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 0.139   -0.228  0.00401 0.370  0.139  
#>  2 1              2 0.0314  -0.201  0.0114  0.0993 0.0314 
#>  3 1              3 0.623   -0.175  0.0289  0.875  0.623  
#>  4 1              4 0.225   -0.148  0.0657  0.528  0.225  
#>  5 1              5 0.370   -0.121  0.135   0.708  0.370  
#>  6 1              6 0.114   -0.0945 0.250   0.315  0.114  
#>  7 1              7 0.157   -0.0679 0.421   0.407  0.157  
#>  8 1              8 0.00425 -0.0412 0.649   0.0141 0.00425
#>  9 1              9 0.0915  -0.0145 0.924   0.263  0.0915 
#> 10 1             10 0.134    0.0122 1.22    0.360  0.134  
#> # ℹ 40 more rows