Tidy Randomly Generated Inverse Weibull Distribution Tibble

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 of n for the current simulation.

• y The randomly generated data point.

• dx The x value from the stats::density() function.

• dy The y value from the stats::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.

Value

A tibble of randomly generated data.

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_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()

Author

Steven P. Sanderson II, MPH

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  2.93  -2.97  0.000702 0.711  2.93 
#>  2 1              2  2.09  -1.68  0.0174   0.620  2.09 
#>  3 1              3 57.4   -0.378 0.110    0.983 57.4  
#>  4 1              4 37.0    0.920 0.206    0.973 37.0  
#>  5 1              5  0.482  2.22  0.159    0.126  0.482
#>  6 1              6  7.41   3.52  0.0763   0.874  7.41 
#>  7 1              7  1.91   4.81  0.0325   0.592  1.91 
#>  8 1              8  7.19   6.11  0.0318   0.870  7.19 
#>  9 1              9  1.06   7.41  0.0399   0.391  1.06 
#> 10 1             10  7.31   8.71  0.0178   0.872  7.31 
#> # ℹ 40 more rows