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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  2.23       -4.62 9.37e- 2 0.625   2.23    
#>  2 1              2  1.43      138.   5.38e- 4 0.557   1.43    
#>  3 1              3  0.295     281.   1.54e- 3 0.317   0.295   
#>  4 1              4  0.000833  424.   4.33e-19 0.0184  0.000833
#>  5 1              5  3.19      567.   6.57e-20 0.675   3.19    
#>  6 1              6  0.358     710.   2.52e-19 0.343   0.358   
#>  7 1              7 13.2       853.   2.44e-21 0.829  13.2     
#>  8 1              8  1.62      996.   0        0.576   1.62    
#>  9 1              9 16.1      1139.   8.54e-19 0.845  16.1     
#> 10 1             10  0.775    1282.   9.53e-20 0.460   0.775   
#> # … with 40 more rows