Tidy Randomly Generated Paralogistic Distribution Tibble

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,
  .return_tibble = TRUE
)

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.
.return_tibble: A logical value indicating whether to return the result as a tibble. Default is TRUE.

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()

Other Continuous Distribution: tidy_beta(), tidy_burr(), tidy_cauchy(), 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_pareto(), tidy_pareto1(), tidy_t(), tidy_triangular(), tidy_uniform(), tidy_weibull(), tidy_zero_truncated_geometric()

Other Logistic: tidy_logistic(), util_logistic_param_estimate(), util_logistic_stats_tbl()

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  1.25  -2.49  0.000878 0.556  1.25 
#>  2 1              2  1.34  -0.936 0.0615   0.573  1.34 
#>  3 1              3  0.981  0.623 0.247    0.495  0.981
#>  4 1              4  2.70   2.18  0.149    0.730  2.70 
#>  5 1              5  1.04   3.74  0.0599   0.510  1.04 
#>  6 1              6  0.251  5.30  0.0371   0.200  0.251
#>  7 1              7 35.6    6.86  0.0101   0.973 35.6  
#>  8 1              8  0.917  8.41  0.000610 0.478  0.917
#>  9 1              9  0.462  9.97  0.00770  0.316  0.462
#> 10 1             10 17.4   11.5   0.00459  0.946 17.4  
#> # ℹ 40 more rows