This function will generate n
random points from a weibull
distribution with a user provided, .shape
, .scale
, 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
Shape parameter defaults to 0.
- .scale
Scale parameter defaults to 1.
- .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 stats::rweibull()
, and its underlying
p
, d
, and q
functions. For more information please see stats::rweibull()
See also
https://www.itl.nist.gov/div898/handbook/eda/section3/eda3669.htm
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_pareto1()
,
tidy_t()
,
tidy_triangular()
,
tidy_uniform()
,
tidy_zero_truncated_geometric()
Other Weibull:
tidy_inverse_weibull()
,
util_weibull_param_estimate()
,
util_weibull_stats_tbl()
Examples
tidy_weibull()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 0.948 -1.17 0.00130 0.613 0.948
#> 2 1 2 1.65 -1.01 0.00448 0.807 1.65
#> 3 1 3 0.155 -0.851 0.0131 0.144 0.155
#> 4 1 4 0.508 -0.691 0.0332 0.398 0.508
#> 5 1 5 2.04 -0.530 0.0723 0.869 2.04
#> 6 1 6 0.803 -0.369 0.136 0.552 0.803
#> 7 1 7 0.889 -0.208 0.224 0.589 0.889
#> 8 1 8 1.34 -0.0469 0.322 0.737 1.34
#> 9 1 9 0.631 0.114 0.411 0.468 0.631
#> 10 1 10 0.318 0.275 0.470 0.272 0.318
#> # ℹ 40 more rows