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This function will generate n random points from a beta distribution with a user provided, .shape1, .shape2, .ncp or non-centrality parameter, 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_beta(.n = 50, .shape1 = 1, .shape2 = 1, .ncp = 0, .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.

.ncp

The non-centrality parameter of the Beta distribution.

.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_beta()
#> # A tibble: 50 × 7
#>    sim_number     x     y      dx      dy     p     q
#>    <fct>      <int> <dbl>   <dbl>   <dbl> <dbl> <dbl>
#>  1 1              1 0.581 -0.364  0.00213 0.581 0.581
#>  2 1              2 0.699 -0.328  0.00505 0.699 0.699
#>  3 1              3 0.862 -0.293  0.0111  0.862 0.862
#>  4 1              4 0.150 -0.258  0.0225  0.150 0.150
#>  5 1              5 0.228 -0.223  0.0427  0.228 0.228
#>  6 1              6 0.949 -0.188  0.0750  0.949 0.949
#>  7 1              7 0.990 -0.152  0.123   0.990 0.990
#>  8 1              8 0.356 -0.117  0.188   0.356 0.356
#>  9 1              9 0.636 -0.0820 0.269   0.636 0.636
#> 10 1             10 0.546 -0.0468 0.362   0.546 0.546
#> # … with 40 more rows