Tidy Randomly Generated T Distribution Tibble

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()

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 -0.0479 -13.4  0.000151 0.485  -0.0479
#>  2 1              2  0.978  -12.2  0.00725  0.746   0.978 
#>  3 1              3 -7.80   -11.0  0.00856  0.0406 -7.80  
#>  4 1              4 -1.10    -9.75 0.000438 0.235  -1.10  
#>  5 1              5 -2.24    -8.52 0.0136   0.134  -2.24  
#>  6 1              6 -1.66    -7.30 0.0323   0.173  -1.66  
#>  7 1              7  1.83    -6.07 0.0122   0.841   1.83  
#>  8 1              8 17.0     -4.85 0.00694  0.981  17.0   
#>  9 1              9 -1.31    -3.63 0.00835  0.208  -1.31  
#> 10 1             10 -0.780   -2.40 0.0546   0.289  -0.780 
#> # ℹ 40 more rows