Skip to contents

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()

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