
Tidy Randomly Generated Inverse Burr Distribution Tibble
Source:R/random-tidy-burr-inverse.R
tidy_inverse_burr.Rd
This function will generate n
random points from an Inverse Burr
distribution with a user provided, .shape1
, .shape2
, .scale
, .rate
, 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.
Usage
tidy_inverse_burr(
.n = 50,
.shape1 = 1,
.shape2 = 1,
.rate = 1,
.scale = 1/.rate,
.num_sims = 1,
.return_tibble = TRUE
)
Arguments
- .n
The number of randomly generated points you want.
- .shape1
Must be strictly positive.
- .shape2
Must be strictly positive.
- .rate
An alternative way to specify the
.scale
.- .scale
Must be strictly positive.
- .num_sims
The number of randomly generated simulations you want.
- .return_tibble
A logical value indicating whether to return the result as a tibble. Default is TRUE.
Details
This function uses the underlying actuar::rinvburr()
, and its underlying
p
, d
, and q
functions. For more information please see actuar::rinvburr()
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_exponential()
,
tidy_inverse_gamma()
,
tidy_inverse_normal()
,
tidy_inverse_pareto()
,
tidy_inverse_weibull()
,
tidy_logistic()
,
tidy_lognormal()
,
tidy_normal()
,
tidy_paralogistic()
,
tidy_pareto()
,
tidy_pareto1()
,
tidy_t()
,
tidy_triangular()
,
tidy_uniform()
,
tidy_weibull()
,
tidy_zero_truncated_geometric()
Other Burr:
tidy_burr()
,
util_burr_param_estimate()
,
util_burr_stats_tbl()
Other Inverse Distribution:
tidy_inverse_exponential()
,
tidy_inverse_gamma()
,
tidy_inverse_normal()
,
tidy_inverse_pareto()
,
tidy_inverse_weibull()
Examples
tidy_inverse_burr()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 0.763 -3.12 0.000778 0.433 0.763
#> 2 1 2 11.4 -2.67 0.00279 0.920 11.4
#> 3 1 3 1.78 -2.21 0.00834 0.640 1.78
#> 4 1 4 3.92 -1.76 0.0210 0.797 3.92
#> 5 1 5 1.58 -1.31 0.0445 0.613 1.58
#> 6 1 6 0.103 -0.862 0.0801 0.0931 0.103
#> 7 1 7 2.36 -0.410 0.123 0.703 2.36
#> 8 1 8 1.94 0.0407 0.164 0.659 1.94
#> 9 1 9 4.62 0.492 0.191 0.822 4.62
#> 10 1 10 1.94 0.943 0.199 0.660 1.94
#> # ℹ 40 more rows