Tidy Randomly Generated Pareto Distribution Tibble

This function will generate n random points from a pareto 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_pareto(
  .n = 50,
  .shape = 10,
  .scale = 0.1,
  .num_sims = 1,
  .return_tibble = TRUE
)

Arguments

.n

The number of randomly generated points you want.

.shape

Must be positive.

.scale

Must be 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 actuar::rpareto(), and its underlying p, d, and q functions. For more information please see actuar::rpareto()

See also

https://openacttexts.github.io/Loss-Data-Analytics/ChapSummaryDistributions.html

Other Continuous Distribution: tidy_beta(), 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_pareto1(), tidy_t(), tidy_triangular(), tidy_uniform(), tidy_weibull(), tidy_zero_truncated_geometric()

Other Pareto: tidy_generalized_pareto(), tidy_inverse_pareto(), tidy_pareto1(), util_pareto1_aic(), util_pareto1_param_estimate(), util_pareto1_stats_tbl(), util_pareto_param_estimate(), util_pareto_stats_tbl()

Author

Steven P. Sanderson II, MPH

Examples

tidy_pareto()
#> # A tibble: 50 × 7
#>    sim_number     x       y        dx     dy     p       q
#>    <fct>      <int>   <dbl>     <dbl>  <dbl> <dbl>   <dbl>
#>  1 1              1 0.0264  -0.00984   0.115 0.904 0.0264 
#>  2 1              2 0.0161  -0.00763   0.815 0.776 0.0161 
#>  3 1              3 0.0213  -0.00542   3.87  0.856 0.0213 
#>  4 1              4 0.00170 -0.00321  12.6   0.155 0.00170
#>  5 1              5 0.00918 -0.000997 28.6   0.585 0.00918
#>  6 1              6 0.00592  0.00121  47.0   0.437 0.00592
#>  7 1              7 0.00550  0.00343  58.3   0.414 0.00550
#>  8 1              8 0.0304   0.00564  58.2   0.930 0.0304 
#>  9 1              9 0.00264  0.00785  49.5   0.229 0.00264
#> 10 1             10 0.00550  0.0101   38.3   0.415 0.00550
#> # ℹ 40 more rows