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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 0.0198  -0.368  0.00643 0.0638 0.0198 
#>  2 1              2 0.00909 -0.331  0.0161  0.0298 0.00909
#>  3 1              3 0.188   -0.293  0.0372  0.465  0.188  
#>  4 1              4 0.178   -0.255  0.0785  0.448  0.178  
#>  5 1              5 0.0401  -0.217  0.152   0.125  0.0401 
#>  6 1              6 0.0384  -0.179  0.272   0.120  0.0384 
#>  7 1              7 0.125   -0.142  0.447   0.341  0.125  
#>  8 1              8 0.319   -0.104  0.678   0.654  0.319  
#>  9 1              9 0.873   -0.0661 0.950   0.945  0.873  
#> 10 1             10 0.102   -0.0283 1.23    0.289  0.102  
#> # … with 40 more rows