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 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::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_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_t()
,
tidy_uniform()
,
tidy_weibull()
,
tidy_zero_truncated_geometric()
Other Pareto:
tidy_generalized_pareto()
,
tidy_inverse_pareto()
,
tidy_pareto1()
,
util_pareto_param_estimate()
,
util_pareto_stats_tbl()
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 0.000429 -0.0110 0.133 0.0419 0.000429
#> 2 1 2 0.000701 -0.00954 0.433 0.0675 0.000701
#> 3 1 3 0.0164 -0.00808 1.22 0.781 0.0164
#> 4 1 4 0.00652 -0.00662 3.01 0.468 0.00652
#> 5 1 5 0.00513 -0.00516 6.46 0.393 0.00513
#> 6 1 6 0.0104 -0.00370 12.1 0.629 0.0104
#> 7 1 7 0.00402 -0.00225 20.1 0.326 0.00402
#> 8 1 8 0.0343 -0.000787 29.5 0.947 0.0343
#> 9 1 9 0.00562 0.000672 38.7 0.421 0.00562
#> 10 1 10 0.000117 0.00213 45.7 0.0116 0.000117
#> # ℹ 40 more rows