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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  0.988 -15.6  2.00e- 4 0.748   0.988
#>  2 1              2  0.922 -14.8  7.85e- 3 0.737   0.922
#>  3 1              3 -2.52  -14.0  1.52e- 2 0.120  -2.52 
#>  4 1              4  0.536 -13.2  1.48e- 3 0.657   0.536
#>  5 1              5 22.6   -12.4  6.92e- 6 0.986  22.6  
#>  6 1              6 -5.46  -11.6  1.83e- 9 0.0576 -5.46 
#>  7 1              7 -0.410 -10.7  1.96e-14 0.376  -0.410
#>  8 1              8  1.74   -9.94 9.86e-14 0.834   1.74 
#>  9 1              9 -0.207  -9.13 5.60e- 9 0.435  -0.207
#> 10 1             10  0.625  -8.32 1.63e- 5 0.678   0.625
#> # ℹ 40 more rows