Tidy Randomly Generated Generalized Pareto Distribution Tibble
Source:R/random-tidy-general-pareto.R
tidy_generalized_pareto.RdThis function will generate n random points from a generalized
Pareto distribution with a user provided, .shape1, .shape2, .rate or
.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_numberThe current simulation number.xThe current value ofnfor the current simulation.yThe randomly generated data point.dxThexvalue from thestats::density()function.dyTheyvalue from thestats::density()function.pThe values from the resulting p_ function of the distribution family.qThe values from the resulting q_ function of the distribution family.
Usage
tidy_generalized_pareto(
.n = 50,
.shape1 = 1,
.shape2 = 1,
.rate = 1,
.scale = 1/.rate,
.num_sims = 1
)Arguments
- .n
The number of randomly generated points you want.
- .shape1
Must be positive.
- .shape2
Must be positive.
- .rate
An alternative way to specify the
.scaleargument- .scale
Must be positive.
- .num_sims
The number of randomly generated simulations you want.
Details
This function uses the underlying actuar::rgenpareto(), and its underlying
p, d, and q functions. For more information please see actuar::rgenpareto()
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_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_pareto1(),
tidy_pareto(),
tidy_t(),
tidy_uniform(),
tidy_weibull(),
tidy_zero_truncated_geometric()
Other Pareto:
tidy_inverse_pareto(),
tidy_pareto1(),
tidy_pareto(),
util_pareto_param_estimate(),
util_pareto_stats_tbl()
Examples
tidy_generalized_pareto()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 3.24 -2.13 0.00102 0.764 3.24
#> 2 1 2 2.89 -1.59 0.00871 0.743 2.89
#> 3 1 3 0.356 -1.05 0.0440 0.263 0.356
#> 4 1 4 3.83 -0.509 0.132 0.793 3.83
#> 5 1 5 4.63 0.0304 0.244 0.823 4.63
#> 6 1 6 0.843 0.570 0.293 0.458 0.843
#> 7 1 7 0.377 1.11 0.251 0.274 0.377
#> 8 1 8 0.372 1.65 0.187 0.271 0.372
#> 9 1 9 1.02 2.19 0.152 0.506 1.02
#> 10 1 10 0.0639 2.73 0.137 0.0600 0.0639
#> # … with 40 more rows