
Tidy Randomly Generated Pareto Single Parameter Distribution Tibble
Source:R/random-tidy-pareto-single-param.R
tidy_pareto1.Rd
This function will generate n
random points from a single parameter
pareto distribution with a user provided, .shape
, .min
, 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.
- .min
The lower bound of the support of the distribution.
- .num_sims
The number of randomly generated simulations you want.
Details
This function uses the underlying actuar::rpareto1()
, and its underlying
p
, d
, and q
functions. For more information please see actuar::rpareto1()
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_pareto()
,
tidy_t()
,
tidy_uniform()
,
tidy_weibull()
,
tidy_zero_truncated_geometric()
Other Pareto:
tidy_generalized_pareto()
,
tidy_inverse_pareto()
,
tidy_pareto()
,
util_pareto_param_estimate()
,
util_pareto_stats_tbl()
Examples
tidy_pareto1()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 2.27 -0.883 0.00148 0.560 2.27
#> 2 1 2 1.41 -0.162 0.0292 0.289 1.41
#> 3 1 3 5.39 0.559 0.177 0.815 5.39
#> 4 1 4 5.38 1.28 0.354 0.814 5.38
#> 5 1 5 2.26 2.00 0.281 0.558 2.26
#> 6 1 6 1.42 2.72 0.153 0.298 1.42
#> 7 1 7 1.31 3.44 0.0887 0.234 1.31
#> 8 1 8 1.35 4.16 0.0615 0.262 1.35
#> 9 1 9 2.43 4.88 0.0664 0.588 2.43
#> 10 1 10 1.85 5.60 0.0588 0.458 1.85
#> # ℹ 40 more rows