
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 3.69 -1.19 0.00133 0.729 3.69
#> 2 1 2 1.57 -0.772 0.00694 0.361 1.57
#> 3 1 3 1.06 -0.350 0.0264 0.0593 1.06
#> 4 1 4 1.27 0.0717 0.0741 0.211 1.27
#> 5 1 5 4.02 0.494 0.155 0.751 4.02
#> 6 1 6 1.80 0.916 0.246 0.445 1.80
#> 7 1 7 1.06 1.34 0.303 0.0528 1.06
#> 8 1 8 1.11 1.76 0.299 0.100 1.11
#> 9 1 9 10.9 2.18 0.247 0.908 10.9
#> 10 1 10 1.02 2.60 0.183 0.0152 1.02
#> # ℹ 40 more rows