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 ofn
for the current simulation.y
The randomly generated data point.dx
Thex
value from thestats::density()
function.dy
They
value from thestats::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.
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.
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()
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