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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()

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  1.87  -10.9  0.000104 0.844  1.87 
#>  2 1              2  0.296 -10.3  0.000691 0.592  0.296
#>  3 1              3  4.59   -9.65 0.00273  0.932  4.59 
#>  4 1              4  1.90   -9.02 0.00646  0.846  1.90 
#>  5 1              5  1.05   -8.40 0.00913  0.758  1.05 
#>  6 1              6  5.65   -7.78 0.00776  0.944  5.65 
#>  7 1              7 -0.119  -7.15 0.00435  0.462 -0.119
#>  8 1              8  0.109  -6.53 0.00366  0.535  0.109
#>  9 1              9 -0.253  -5.91 0.00867  0.421 -0.253
#> 10 1             10 -1.11   -5.29 0.0191   0.233 -1.11 
#> # … with 40 more rows