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 2.67 -1.28 0.00109 0.625 2.67
#> 2 1 2 2.02 -0.805 0.00640 0.504 2.02
#> 3 1 3 1.20 -0.331 0.0264 0.163 1.20
#> 4 1 4 5.46 0.142 0.0775 0.817 5.46
#> 5 1 5 2.37 0.616 0.163 0.577 2.37
#> 6 1 6 1.68 1.09 0.252 0.406 1.68
#> 7 1 7 2.58 1.56 0.295 0.613 2.58
#> 8 1 8 1.30 2.04 0.273 0.228 1.30
#> 9 1 9 19.6 2.51 0.213 0.949 19.6
#> 10 1 10 1.03 2.98 0.152 0.0331 1.03
#> # … with 40 more rows