
Tidy Randomly Generated Inverse Pareto Distribution Tibble
Source:R/random-tidy-pareto-inverse.R
tidy_inverse_pareto.Rd
This function will generate n
random points from an inverse
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 ofn
for the current simulation.y
The randomly generated data point.dx
Thex
value from thestats::density()
function.dy
They
value from thestats::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.
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.
Details
This function uses the underlying actuar::rinvpareto()
, and its underlying
p
, d
, and q
functions. For more information please see actuar::rinvpareto()
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_geometric()
,
tidy_inverse_burr()
,
tidy_inverse_exponential()
,
tidy_inverse_gamma()
,
tidy_inverse_normal()
,
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_generalized_pareto()
,
tidy_pareto1()
,
tidy_pareto()
,
util_pareto_param_estimate()
,
util_pareto_stats_tbl()
Other Inverse Distribution:
tidy_inverse_burr()
,
tidy_inverse_exponential()
,
tidy_inverse_gamma()
,
tidy_inverse_normal()
,
tidy_inverse_weibull()
Examples
tidy_inverse_pareto()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 0.477 -1.74 0.00124 0.323 0.477
#> 2 1 2 0.0281 -1.03 0.0306 0.0273 0.0281
#> 3 1 3 0.101 -0.310 0.191 0.0914 0.101
#> 4 1 4 2.21 0.405 0.348 0.689 2.21
#> 5 1 5 1.88 1.12 0.266 0.653 1.88
#> 6 1 6 0.622 1.84 0.167 0.383 0.622
#> 7 1 7 1.61 2.55 0.0899 0.617 1.61
#> 8 1 8 0.445 3.27 0.0506 0.308 0.445
#> 9 1 9 0.578 3.98 0.0364 0.366 0.578
#> 10 1 10 0.787 4.70 0.0284 0.441 0.787
#> # ℹ 40 more rows