This function will generate n random points from a logisitc distribution with a user provided, rate, and number of random simulations to be produced. The function returns a tibble with the simulation number column the x column which corresonds 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.

tidy_logisitc(.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

.num_sims

The number of randomly generated simulations you want.

Value

A tibble of randomly generated data.

Details

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

Author

Steven P. Sanderson II, MPH

Examples

tidy_logisitc()
#> # A tibble: 50 x 7
#>    sim_number     x      y    dx       dy        p       q
#>    <fct>      <int>  <dbl> <dbl>    <dbl>    <dbl>   <dbl>
#>  1 1              1  1.58  -6.47 0.000148 1.93e-22 -Inf   
#>  2 1              2 -1.94  -6.20 0.000500 1.43e-21   -3.87
#>  3 1              3 -1.94  -5.94 0.00140  1.05e-20   -3.16
#>  4 1              4 -0.579 -5.67 0.00330  7.78e-20   -2.73
#>  5 1              5 -0.376 -5.41 0.00657  5.75e-19   -2.42
#>  6 1              6  1.00  -5.14 0.0112   4.25e-18   -2.17
#>  7 1              7 -0.451 -4.88 0.0169   3.14e-17   -1.97
#>  8 1              8 -0.190 -4.61 0.0227   2.32e-16   -1.79
#>  9 1              9  0.108 -4.35 0.0279   1.71e-15   -1.63
#> 10 1             10  0.645 -4.08 0.0312   1.27e-14   -1.49
#> # ... with 40 more rows