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_numberThe current simulation number.xThe current value ofnfor the current simulation.yThe randomly generated data point.dxThexvalue from thestats::density()function.dyTheyvalue from thestats::density()function.pThe values from the resulting p_ function of the distribution family.qThe 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 2.08 -5.23 9.28e- 4 0.857 2.08
#> 2 1 2 2.43 7.16 1.12e- 6 0.876 2.43
#> 3 1 3 0.163 19.5 6.94e-11 0.551 0.163
#> 4 1 4 0.801 31.9 0 0.715 0.801
#> 5 1 5 -0.255 44.3 8.71e-19 0.421 -0.255
#> 6 1 6 -1.12 56.7 2.70e-18 0.233 -1.12
#> 7 1 7 0.0980 69.1 2.11e-18 0.531 0.0980
#> 8 1 8 3.11 81.5 0 0.901 3.11
#> 9 1 9 2.67 93.8 0 0.886 2.67
#> 10 1 10 0.453 106. 1.03e-18 0.636 0.453
#> # … with 40 more rows