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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 0.541  -3.36   0.000925 0.351  0.541 
#>  2 1              2 6.19   -2.54   0.00696  0.861  6.19  
#>  3 1              3 1.16   -1.71   0.0318   0.538  1.16  
#>  4 1              4 0.565  -0.891  0.0882   0.361  0.565 
#>  5 1              5 0.947  -0.0693 0.155    0.486  0.947 
#>  6 1              6 0.0751  0.753  0.183    0.0699 0.0751
#>  7 1              7 1.20    1.57   0.162    0.545  1.20  
#>  8 1              8 1.69    2.40   0.126    0.628  1.69  
#>  9 1              9 4.92    3.22   0.0922   0.831  4.92  
#> 10 1             10 3.65    4.04   0.0635   0.785  3.65  
#> # ℹ 40 more rows