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# Tidy Randomly Generated Cauchy Distribution Tibble

Source: `R/random-tidy-cauchy.R`
`tidy_cauchy.Rd`

This function will generate `n` random points from a cauchy distribution with a user provided, `.location`, `.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_cauchy(
      .n = 50,
      .location = 0,
      .scale = 1,
      .num_sims = 1,
      .return_tibble = TRUE
    )

## Arguments

.n

  The number of randomly generated points you want.

.location

  The location parameter.

.scale

  The scale parameter, must be greater than or equal to 0.

.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 `stats::rcauchy()`, and its underlying `p`, `d`, and `q` functions. For more information please see `stats::rcauchy()`

## See also

https://www.itl.nist.gov/div898/handbook/eda/section3/eda3663.htm

Other Continuous Distribution: `tidy_beta()`, `tidy_burr()`, `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_weibull()`, `tidy_zero_truncated_geometric()`

Other Cauchy: `util_cauchy_param_estimate()`, `util_cauchy_stats_tbl()`

## Author

Steven P. Sanderson II, MPH

## Examples

    tidy_cauchy()
    #> # A tibble: 50 × 7
    #>    sim_number     x       y     dx       dy      p       q
    #>    <fct>      <int>   <dbl>  <dbl>    <dbl>  <dbl>   <dbl>
    #>  1 1              1 -1.14   -107.  2.50e- 4 0.229  -1.14
    #>  2 1              2 -2.15   -103.  2.91e- 5 0.138  -2.15
    #>  3 1              3 -3.73    -98.9 0        0.0833 -3.73
    #>  4 1              4  2.25    -94.9 6.56e-20 0.867   2.25
    #>  5 1              5  0.0564  -91.0 1.51e-18 0.518   0.0564
    #>  6 1              6  0.686   -87.1 4.19e-18 0.691   0.686
    #>  7 1              7 -0.325   -83.2 0        0.400  -0.325
    #>  8 1              8 -0.456   -79.3 6.52e-19 0.364  -0.456
    #>  9 1              9  3.66    -75.4 0        0.915   3.66
    #> 10 1             10  0.0966  -71.5 1.48e-18 0.531   0.0966
    #> # ℹ 40 more rows