Tidy Randomly Generated T Distribution Tibble — tidy_t • TidyDensity
Description: 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.

Skip to contents

# 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)

## 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()`

## 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_pareto1()`, `tidy_pareto()`, `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 -1.03   -24.5  1.47e- 4 0.245 -1.03
    #>  2 1              2  0.510  -22.1  9.75e- 3 0.650  0.510
    #>  3 1              3  1.75   -19.7  1.73e- 6 0.835  1.75
    #>  4 1              4  1.60   -17.3  6.88e- 8 0.822  1.60
    #>  5 1              5 -0.959  -14.9  4.84e- 3 0.257 -0.959
    #>  6 1              6  0.287  -12.5  1.00e- 3 0.589  0.287
    #>  7 1              7 -0.850  -10.1  7.17e-10 0.276 -0.850
    #>  8 1              8 -0.356   -7.69 3.43e- 4 0.391 -0.356
    #>  9 1              9  0.0557  -5.29 8.68e- 3 0.518  0.0557
    #> 10 1             10 10.7     -2.89 2.82e- 2 0.970 10.7
    #> # ℹ 40 more rows