Tidy Randomly Generated Weibull Distribution Tibble

This function will generate n random points from a weibull 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_weibull(
  .n = 50,
  .shape = 1,
  .scale = 1,
  .num_sims = 1,
  .return_tibble = TRUE
)

Arguments

.n: The number of randomly generated points you want.
.shape: Shape parameter defaults to 0.
.scale: Scale parameter defaults to 1.
.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::rweibull(), and its underlying p, d, and q functions. For more information please see stats::rweibull()

Other Continuous Distribution: tidy_beta(), tidy_burr(), tidy_cauchy(), tidy_chisquare(), tidy_exponential(), tidy_f(), tidy_gamma(), tidy_generalized_beta(), 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_zero_truncated_geometric()

Other Weibull: tidy_inverse_weibull(), util_weibull_param_estimate(), util_weibull_stats_tbl()

Author

Steven P. Sanderson II, MPH

Examples

tidy_weibull()
#> # A tibble: 50 × 7
#>    sim_number     x     y      dx      dy     p     q
#>    <fct>      <int> <dbl>   <dbl>   <dbl> <dbl> <dbl>
#>  1 1              1 0.948 -1.17   0.00130 0.613 0.948
#>  2 1              2 1.65  -1.01   0.00448 0.807 1.65 
#>  3 1              3 0.155 -0.851  0.0131  0.144 0.155
#>  4 1              4 0.508 -0.691  0.0332  0.398 0.508
#>  5 1              5 2.04  -0.530  0.0723  0.869 2.04 
#>  6 1              6 0.803 -0.369  0.136   0.552 0.803
#>  7 1              7 0.889 -0.208  0.224   0.589 0.889
#>  8 1              8 1.34  -0.0469 0.322   0.737 1.34 
#>  9 1              9 0.631  0.114  0.411   0.468 0.631
#> 10 1             10 0.318  0.275  0.470   0.272 0.318
#> # ℹ 40 more rows