Tidy Randomly Generated Weibull Distribution Tibble — tidy_weibull • TidyDensity
Description: 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 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.

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# Tidy Randomly Generated Weibull Distribution Tibble

Source: `R/random-tidy-weibull.R`
`tidy_weibull.Rd`

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 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_weibull(.n = 50, .shape = 1, .scale = 1, .num_sims = 1)

## 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.

## Value

A tibble of randomly generated data.

## 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_pareto1()`, `tidy_pareto()`, `tidy_t()`, `tidy_uniform()`, `tidy_zero_truncated_geometric()`

Other Weibull: `tidy_inverse_weibull()`, `util_weibull_param_estimate()`, `util_weibull_stats_tbl()`

## Author

Steven P. Sanderson II, MPH

## 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 1.63  -1.03   0.00253 0.805 1.63
    #>  2 1              2 0.113 -0.890  0.00844 0.107 0.113
    #>  3 1              3 0.519 -0.748  0.0242  0.405 0.519
    #>  4 1              4 0.321 -0.607  0.0596  0.275 0.321
    #>  5 1              5 4.86  -0.465  0.126   0.992 4.86
    #>  6 1              6 0.190 -0.323  0.229   0.173 0.190
    #>  7 1              7 0.136 -0.181  0.361   0.127 0.136
    #>  8 1              8 0.317 -0.0397 0.493   0.271 0.317
    #>  9 1              9 1.22   0.102  0.588   0.705 1.22
    #> 10 1             10 2.14   0.244  0.618   0.883 2.14
    #> # ℹ 40 more rows