Tidy Randomly Generated Geometric Distribution Tibble — tidy_geometric • TidyDensity
Description: This function will generate n random points from a geometric distribution with a user provided, .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 Geometric Distribution Tibble

Source: `R/random-tidy-geom.R`
`tidy_geometric.Rd`

This function will generate `n` random points from a geometric distribution with a user provided, `.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_geometric(.n = 50, .prob = 1, .num_sims = 1)

## Arguments

.n

  The number of randomly generated points you want.

.prob

  A probability of success in 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 `stats::rgeom()`, and its underlying `p`, `d`, and `q` functions. For more information please see `stats::rgeom()`

## See also

https://en.wikipedia.org/wiki/Geometric_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_inverse_burr()`, `tidy_inverse_exponential()`, `tidy_inverse_gamma()`, `tidy_inverse_normal()`, `tidy_inverse_pareto()`, `tidy_inverse_weibull()`, `tidy_logistic()`, `tidy_lognormal()`, `tidy_normal()`, `tidy_paralogistic()`, `tidy_pareto1()`, `tidy_pareto()`, `tidy_t()`, `tidy_uniform()`, `tidy_weibull()`, `tidy_zero_truncated_geometric()`

Other Geometric: `tidy_zero_truncated_geometric()`, `util_geometric_param_estimate()`, `util_geometric_stats_tbl()`

## Author

Steven P. Sanderson II, MPH

## Examples

    tidy_geometric()
    #> # A tibble: 50 × 7
    #>    sim_number     x     y     dx     dy     p     q
    #>    <fct>      <int> <int>  <dbl>  <dbl> <dbl> <dbl>
    #>  1 1              1     0 -1.23  0.0109     1     0
    #>  2 1              2     0 -1.18  0.0156     1     0
    #>  3 1              3     0 -1.13  0.0220     1     0
    #>  4 1              4     0 -1.08  0.0305     1     0
    #>  5 1              5     0 -1.03  0.0418     1     0
    #>  6 1              6     0 -0.983 0.0564     1     0
    #>  7 1              7     0 -0.932 0.0749     1     0
    #>  8 1              8     0 -0.882 0.0981     1     0
    #>  9 1              9     0 -0.832 0.126      1     0
    #> 10 1             10     0 -0.781 0.161      1     0
    #> # ℹ 40 more rows