Tidy Randomly Generated Cauchy Distribution Tibble — tidy_cauchy • TidyDensity
Description: 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.

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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)

## 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.

## 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_pareto1()`, `tidy_pareto()`, `tidy_t()`, `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  -1.23   -12.0  0.000203      0.217   -1.23
    #>  2 1              2   0.603  -11.6  0.00226       0.673    0.603
    #>  3 1              3  -0.520  -11.2  0.0101        0.347   -0.520
    #>  4 1              4  -4.56   -10.8  0.0179        0.0687  -4.56
    #>  5 1              5   0.122  -10.3  0.0126        0.539    0.122
    #>  6 1              6   0.131   -9.92 0.00357       0.541    0.131
    #>  7 1              7   0.454   -9.50 0.000403      0.636    0.454
    #>  8 1              8 -10.7     -9.07 0.0000181     0.0296 -10.7
    #>  9 1              9   2.45    -8.64 0.000000326   0.876    2.45
    #> 10 1             10  -0.0710  -8.22 0.00000000233 0.477   -0.0710
    #> # ℹ 40 more rows