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# Tidy Randomly Generated F Distribution Tibble

Source: `R/random-tidy-f.R`
`tidy_f.Rd`

This function will generate `n` random points from a rf distribution with a user provided, `df1`,`df2`, and `ncp`, 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_f(
      .n = 50,
      .df1 = 1,
      .df2 = 1,
      .ncp = 0,
      .num_sims = 1,
      .return_tibble = TRUE
    )

## Arguments

.n

  The number of randomly generated points you want.

.df1

  Degrees of freedom, Inf is allowed.

.df2

  Degrees of freedom, Inf is allowed.

.ncp

  Non-centrality parameter.

.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 `stats::rf()`, and its underlying `p`, `d`, and `q` functions. For more information please see `stats::rf()`

## See also

https://www.itl.nist.gov/div898/handbook/eda/section3/eda3665.htm

Other Continuous Distribution: `tidy_beta()`, `tidy_burr()`, `tidy_cauchy()`, `tidy_chisquare()`, `tidy_exponential()`, `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_paralogistic()`, `tidy_pareto()`, `tidy_pareto1()`, `tidy_t()`, `tidy_triangular()`, `tidy_uniform()`, `tidy_weibull()`, `tidy_zero_truncated_geometric()`

Other F Distribution: `util_f_stats_tbl()`

## Author

Steven P. Sanderson II, MPH

## Examples

    tidy_f()
    #> # A tibble: 50 × 7
    #>    sim_number     x         y     dx       dy      p         q
    #>    <fct>      <int>     <dbl>  <dbl>    <dbl>  <dbl>     <dbl>
    #>  1 1              1   4.66    -4.09  0.00124  0.724    4.66
    #>  2 1              2   0.107   -0.794 0.120    0.201    0.107
    #>  3 1              3   3.22     2.50  0.0981   0.676    3.22
    #>  4 1              4   0.159    5.79  0.0151   0.242    0.159
    #>  5 1              5   0.00313  9.08  0.00921  0.0356   0.00313
    #>  6 1              6   0.181   12.4   0.00443  0.256    0.181
    #>  7 1              7  14.7     15.7   0.0104   0.838   14.7
    #>  8 1              8   0.762   19.0   0.000345 0.457    0.762
    #>  9 1              9 107.      22.3   0.00320  0.939  107.
    #> 10 1             10   0.167   25.5   0.00867  0.247    0.167
    #> # ℹ 40 more rows