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This function will generate n random points from a rt distribution with a user provided, df, 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_t(.n = 50, .df = 1, .ncp = 0, .num_sims = 1)

Arguments

.n

The number of randomly generated points you want.

.df

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

Author

Steven P. Sanderson II, MPH

Examples

tidy_t()
#> # A tibble: 50 × 7
#>    sim_number     x        y    dx       dy      p        q
#>    <fct>      <int>    <dbl> <dbl>    <dbl>  <dbl>    <dbl>
#>  1 1              1  0.987   -52.4 1.40e- 4 0.748   0.987  
#>  2 1              2  1.81    -50.9 8.32e- 3 0.839   1.81   
#>  3 1              3 -2.38    -49.4 4.89e- 3 0.127  -2.38   
#>  4 1              4 -3.17    -48.0 2.78e- 5 0.0972 -3.17   
#>  5 1              5 -1.15    -46.5 1.83e- 9 0.227  -1.15   
#>  6 1              6 -4.39    -45.0 1.10e-15 0.0712 -4.39   
#>  7 1              7  0.101   -43.6 6.12e-18 0.532   0.101  
#>  8 1              8  0.949   -42.1 9.51e-18 0.742   0.949  
#>  9 1              9 -0.00296 -40.6 6.27e-18 0.499  -0.00296
#> 10 1             10 -0.867   -39.2 0        0.273  -0.867  
#> # ℹ 40 more rows