Tidy Randomly Generated F Distribution Tibble — tidy_f • TidyDensity
Description: 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.

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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)

## 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.

## 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_pareto1()`, `tidy_pareto()`, `tidy_t()`, `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  2.90    -6.90  0.000804 0.662   2.90
    #>  2 1              2  2.94    -5.42  0.00482  0.664   2.94
    #>  3 1              3 25.9     -3.93  0.0193   0.876  25.9
    #>  4 1              4  0.00685 -2.44  0.0517   0.0526  0.00685
    #>  5 1              5  1.56    -0.952 0.0929   0.571   1.56
    #>  6 1              6  0.914    0.537 0.113    0.486   0.914
    #>  7 1              7  0.244    2.02  0.0956   0.292   0.244
    #>  8 1              8  0.0129   3.51  0.0606   0.0720  0.0129
    #>  9 1              9  0.731    5.00  0.0367   0.450   0.731
    #> 10 1             10  5.32     6.49  0.0301   0.740   5.32
    #> # ℹ 40 more rows