Tidy Randomly Generated Paralogistic Distribution Tibble — tidy_paralogistic • TidyDensity
Description: 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.

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# Tidy Randomly Generated Paralogistic Distribution Tibble

Source: `R/random-tidy-paralogistic.R`
`tidy_paralogistic.Rd`

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()`

## See also

https://en.wikipedia.org/wiki/Logistic_distribution

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_pareto1()`, `tidy_pareto()`, `tidy_t()`, `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  0.330 -3.05  0.00111      0.248  0.330
    #>  2 1              2  3.75   0.619 0.226        0.789  3.75
    #>  3 1              3  4.72   4.28  0.0604       0.825  4.72
    #>  4 1              4 27.2    7.95  0.00488      0.965 27.2
    #>  5 1              5  0.237 11.6   0.00842      0.192  0.237
    #>  6 1              6  0.557 15.3   0.00290      0.358  0.557
    #>  7 1              7  3.21  18.9   0.0000000368 0.762  3.21
    #>  8 1              8  1.52  22.6   0.000000415  0.604  1.52
    #>  9 1              9  2.36  26.3   0.00605      0.702  2.36
    #> 10 1             10  0.127 29.9   0.00281      0.113  0.127
    #> # ℹ 40 more rows