Tidy Randomly Generated Beta Distribution Tibble

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,
  .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.
.ncp: The non-centrality parameter of the Beta distribution.
.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_burr(), tidy_cauchy(), tidy_chisquare(), tidy_exponential(), tidy_f(), tidy_gamma(), tidy_generalized_beta(), tidy_generalized_pareto(), 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_generalized_beta(), util_beta_param_estimate(), util_beta_stats_tbl()

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 0.419 -0.377  0.00316 0.419 0.419
#>  2 1              2 0.229 -0.341  0.00749 0.229 0.229
#>  3 1              3 0.710 -0.305  0.0165  0.710 0.710
#>  4 1              4 0.737 -0.270  0.0336  0.737 0.737
#>  5 1              5 0.497 -0.234  0.0635  0.497 0.497
#>  6 1              6 0.995 -0.198  0.112   0.995 0.995
#>  7 1              7 0.252 -0.162  0.182   0.252 0.252
#>  8 1              8 0.336 -0.127  0.276   0.336 0.336
#>  9 1              9 0.451 -0.0911 0.392   0.451 0.451
#> 10 1             10 0.497 -0.0553 0.519   0.497 0.497
#> # ℹ 40 more rows