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This function will generate n random points from a generalized beta distribution with a user provided, .shape1, .shape2, .shape3, .rate, and/or .sclae, 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_generalized_beta(
  .n = 50,
  .shape1 = 1,
  .shape2 = 1,
  .shape3 = 1,
  .rate = 1,
  .scale = 1/.rate,
  .num_sims = 1
)

Arguments

.n

The number of randomly generated points you want.

.shape1

A non-negative parameter of the Beta distribution.

.shape2

A non-negative parameter of the Beta distribution.

.shape3

A non-negative parameter of the Beta distribution.

.rate

An alternative way to specify the .scale parameter.

.scale

Must be strictly positive.

.num_sims

The number of randomly generated simulations you want.

Value

A tibble of randomly generated data.

Details

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

Author

Steven P. Sanderson II, MPH

Examples

tidy_generalized_beta()
#> # A tibble: 50 × 7
#>    sim_number     x     y      dx      dy     p     q
#>    <fct>      <int> <dbl>   <dbl>   <dbl> <dbl> <dbl>
#>  1 1              1 0.758 -0.330  0.00205 0.758 0.758
#>  2 1              2 0.552 -0.296  0.00475 0.552 0.552
#>  3 1              3 0.710 -0.261  0.0102  0.710 0.710
#>  4 1              4 0.977 -0.226  0.0207  0.977 0.977
#>  5 1              5 0.652 -0.191  0.0390  0.652 0.652
#>  6 1              6 0.256 -0.157  0.0690  0.256 0.256
#>  7 1              7 0.435 -0.122  0.114   0.435 0.435
#>  8 1              8 0.970 -0.0873 0.177   0.970 0.970
#>  9 1              9 0.979 -0.0526 0.259   0.979 0.979
#> 10 1             10 0.883 -0.0179 0.355   0.883 0.883
#> # ℹ 40 more rows