Skip to contents

This function will generate n random points from a paralogistic distribution with a user provided, .shape, .rate, .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_paralogistic(
  .n = 50,
  .shape = 1,
  .rate = 1,
  .scale = 1/.rate,
  .num_sims = 1
)

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.

Value

A tibble of randomly generated data.

Details

This function uses the underlying actuar::rparalogis(), and its underlying p, d, and q functions. For more information please see actuar::rparalogis()

Author

Steven P. Sanderson II, MPH

Examples

tidy_paralogistic()
#> # A tibble: 50 × 7
#>    sim_number     x      y      dx      dy      p      q
#>    <fct>      <int>  <dbl>   <dbl>   <dbl>  <dbl>  <dbl>
#>  1 1              1 5.41   -1.59   0.00130 0.844  5.41  
#>  2 1              2 0.899  -1.34   0.00519 0.473  0.899 
#>  3 1              3 1.44   -1.09   0.0169  0.590  1.44  
#>  4 1              4 1.21   -0.843  0.0452  0.548  1.21  
#>  5 1              5 6.00   -0.594  0.0990  0.857  6.00  
#>  6 1              6 0.0825 -0.345  0.179   0.0762 0.0825
#>  7 1              7 1.92   -0.0959 0.270   0.658  1.92  
#>  8 1              8 0.0927  0.153  0.345   0.0848 0.0927
#>  9 1              9 0.0193  0.402  0.381   0.0189 0.0193
#> 10 1             10 0.279   0.651  0.374   0.218  0.279 
#> # … with 40 more rows