
Tidy Randomly Generated Inverse Weibull Distribution Tibble
Source:R/random-tidy-weibull-inverse.R
tidy_inverse_weibull.Rd
This function will generate n
random points from a weibull
distribution with a user provided, .shape
, .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_weibull(
.n = 50,
.shape = 1,
.rate = 1,
.scale = 1/.rate,
.num_sims = 1,
.return_tibble = TRUE
)
Arguments
- .n
The number of randomly generated points you want.
- .shape
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::rinvweibull()
, and its underlying
p
, d
, and q
functions. For more information please see actuar::rinvweibull()
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_logistic()
,
tidy_lognormal()
,
tidy_normal()
,
tidy_paralogistic()
,
tidy_pareto()
,
tidy_pareto1()
,
tidy_t()
,
tidy_triangular()
,
tidy_uniform()
,
tidy_weibull()
,
tidy_zero_truncated_geometric()
Other Weibull:
tidy_weibull()
,
util_weibull_param_estimate()
,
util_weibull_stats_tbl()
Other Inverse Distribution:
tidy_inverse_burr()
,
tidy_inverse_exponential()
,
tidy_inverse_gamma()
,
tidy_inverse_normal()
,
tidy_inverse_pareto()
Examples
tidy_inverse_weibull()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 2.27 -2.60 0.000536 0.643 2.27
#> 2 1 2 1.73 -1.10 0.0321 0.561 1.73
#> 3 1 3 68.0 0.394 0.204 0.985 68.0
#> 4 1 4 1.13 1.89 0.190 0.413 1.13
#> 5 1 5 2.76 3.39 0.0830 0.696 2.76
#> 6 1 6 0.891 4.89 0.0453 0.325 0.891
#> 7 1 7 16.5 6.38 0.0163 0.941 16.5
#> 8 1 8 2.61 7.88 0.00316 0.682 2.61
#> 9 1 9 1.04 9.38 0.00539 0.381 1.04
#> 10 1 10 1.32 10.9 0.00703 0.470 1.32
#> # ℹ 40 more rows