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# Tidy Randomly Generated T Distribution Tibble

Source: `R/random-tidy-t.R`
`tidy_t.Rd`

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, .return_tibble = TRUE)

## 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.

.return_tibble

  A logical value indicating whether to return the result as a tibble. Default is TRUE.

## 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()`

## See also

https://www.itl.nist.gov/div898/handbook/eda/section3/eda3664.htm

Other Continuous Distribution: `tidy_beta()`, `tidy_burr()`, `tidy_cauchy()`, `tidy_chisquare()`, `tidy_exponential()`, `tidy_f()`, `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_pareto()`, `tidy_pareto1()`, `tidy_triangular()`, `tidy_uniform()`, `tidy_weibull()`, `tidy_zero_truncated_geometric()`

Other T Distribution: `util_t_stats_tbl()`

## 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 -0.844  -5.85 1.22e- 3 0.277 -0.844
    #>  2 1              2 -0.0824 -1.00 1.46e- 1 0.474 -0.0824
    #>  3 1              3  2.83    3.84 4.17e- 2 0.892  2.83
    #>  4 1              4  1.33    8.69 0        0.795  1.33
    #>  5 1              5  1.44   13.5  3.33e-19 0.807  1.44
    #>  6 1              6  0.167  18.4  0        0.553  0.167
    #>  7 1              7  3.72   23.2  1.76e-19 0.916  3.72
    #>  8 1              8 -1.01   28.1  1.18e-19 0.249 -1.01
    #>  9 1              9 -0.790  32.9  0        0.287 -0.790
    #> 10 1             10 -0.662  37.8  7.26e-19 0.314 -0.662
    #> # ℹ 40 more rows