Tidy Randomly Generated Generalized Beta Distribution Tibble

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,
  .return_tibble = TRUE
)

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.
.return_tibble: A logical value indicating whether to return the result as a tibble. Default is TRUE.

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()

Other Continuous Distribution: tidy_beta(), tidy_burr(), tidy_cauchy(), tidy_chisquare(), tidy_exponential(), tidy_f(), tidy_gamma(), tidy_generalized_pareto(), tidy_geometric(), tidy_inverse_burr(), tidy_inverse_exponential(), tidy_inverse_gamma(), tidy_inverse_normal(), tidy_inverse_pareto(), tidy_inverse_weibull(), tidy_logistic(), tidy_lognormal(), tidy_normal(), tidy_paralogistic(), tidy_pareto(), tidy_pareto1(), tidy_t(), tidy_triangular(), tidy_uniform(), tidy_weibull(), tidy_zero_truncated_geometric()

Other Beta: tidy_beta(), util_beta_param_estimate(), util_beta_stats_tbl()

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 0.248  -0.272  0.00334 0.248  0.248 
#>  2 1              2 0.939  -0.241  0.00835 0.939  0.939 
#>  3 1              3 0.852  -0.209  0.0191  0.852  0.852 
#>  4 1              4 0.197  -0.178  0.0398  0.197  0.197 
#>  5 1              5 0.728  -0.146  0.0757  0.728  0.728 
#>  6 1              6 0.963  -0.115  0.132   0.963  0.963 
#>  7 1              7 0.800  -0.0830 0.210   0.800  0.800 
#>  8 1              8 0.353  -0.0515 0.306   0.353  0.353 
#>  9 1              9 0.0827 -0.0199 0.410   0.0827 0.0827
#> 10 1             10 0.807   0.0116 0.506   0.807  0.807 
#> # ℹ 40 more rows