This function will generate n
random points from a 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.
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.
Details
This function uses the underlying actuar::rburr()
, and its underlying
p
, d
, and q
functions. For more information please see actuar::rburr()
See also
https://openacttexts.github.io/Loss-Data-Analytics/ChapSummaryDistributions.html
Other Continuous Distribution:
tidy_beta()
,
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_pareto()
,
tidy_t()
,
tidy_uniform()
,
tidy_weibull()
,
tidy_zero_truncated_geometric()
Other Burr:
tidy_inverse_burr()
,
util_burr_param_estimate()
,
util_burr_stats_tbl()
Examples
tidy_burr()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 167. -2.78 1.53e- 3 0.994 167.
#> 2 1 2 0.575 0.752 2.26e- 1 0.365 0.575
#> 3 1 3 35.8 4.28 4.79e- 2 0.973 35.8
#> 4 1 4 0.000750 7.81 1.90e- 2 0.000749 0.000750
#> 5 1 5 3.02 11.3 3.48e- 6 0.751 3.02
#> 6 1 6 0.136 14.9 9.52e-16 0.120 0.136
#> 7 1 7 7.57 18.4 8.42e-19 0.883 7.57
#> 8 1 8 130. 21.9 0 0.992 130.
#> 9 1 9 1.43 25.5 0 0.589 1.43
#> 10 1 10 0.532 29.0 9.48e-14 0.347 0.532
#> # ℹ 40 more rows