Tidy Randomly Generated Binomial Distribution Tibble — tidy_zero_truncated_negative_binomial • TidyDensity
Description: This function will generate n random points from a zero truncated binomial distribution with a user provided, .size, .prob, 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 Binomial Distribution Tibble

Source: `R/random-zero-trunc-negative-binomial.R`
`tidy_zero_truncated_negative_binomial.Rd`

This function will generate `n` random points from a zero truncated binomial distribution with a user provided, `.size`, `.prob`, 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_zero_truncated_negative_binomial(
      .n = 50,
      .size = 0,
      .prob = 1,
      .num_sims = 1
    )

## Arguments

.n

  The number of randomly generated points you want.

.size

  Number of trials, zero or more.

.prob

  Probability of success on each trial 0 <= prob <= 1.

.num_sims

  The number of randomly generated simulations you want.

## Value

A tibble of randomly generated data.

## Details

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

## See also

https://openacttexts.github.io/Loss-Data-Analytics/ChapSummaryDistributions.html

Other Discrete Distribution: `tidy_bernoulli()`, `tidy_binomial()`, `tidy_hypergeometric()`, `tidy_negative_binomial()`, `tidy_poisson()`, `tidy_zero_truncated_binomial()`, `tidy_zero_truncated_poisson()`

Other Binomial: `tidy_binomial()`, `tidy_negative_binomial()`, `tidy_zero_truncated_binomial()`, `util_binomial_param_estimate()`, `util_binomial_stats_tbl()`, `util_negative_binomial_param_estimate()`

## Author

Steven P. Sanderson II, MPH

## Examples

    tidy_zero_truncated_negative_binomial()
    #> # A tibble: 50 × 7
    #>    sim_number     x     y      dx     dy     p     q
    #>    <fct>      <int> <int>   <dbl>  <dbl> <dbl> <dbl>
    #>  1 1              1     1 -0.235  0.0109     1     1
    #>  2 1              2     1 -0.184  0.0156     1     1
    #>  3 1              3     1 -0.134  0.0220     1     1
    #>  4 1              4     1 -0.0835 0.0305     1     1
    #>  5 1              5     1 -0.0331 0.0418     1     1
    #>  6 1              6     1  0.0173 0.0564     1     1
    #>  7 1              7     1  0.0677 0.0749     1     1
    #>  8 1              8     1  0.118  0.0981     1     1
    #>  9 1              9     1  0.168  0.126      1     1
    #> 10 1             10     1  0.219  0.161      1     1
    #> # ℹ 40 more rows