
Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble
Source:R/random-tidy-chisquare.R
tidy_chisquare.RdThis function will generate n random points from a chisquare
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 (non-negative but can be non-integer)
- .ncp
Non-centrality parameter, must be non-negative.
- .num_sims
The number of randomly generated simulations you want.
Details
This function uses the underlying stats::rchisq(), and its underlying
p, d, and q functions. For more information please see stats::rchisq()
See also
https://www.itl.nist.gov/div898/handbook/eda/section3/eda3666.htm
Other Continuous Distribution:
tidy_beta(),
tidy_burr(),
tidy_cauchy(),
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_t(),
tidy_uniform(),
tidy_weibull(),
tidy_zero_truncated_geometric()
Other Chisquare:
util_chisquare_stats_tbl()
Examples
tidy_chisquare()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 0.167 -2.69 0.00134 0.198 0.167
#> 2 1 2 0.926 -2.26 0.00542 0.460 0.926
#> 3 1 3 2.63 -1.83 0.0176 0.729 2.63
#> 4 1 4 0.0326 -1.40 0.0461 0.0874 0.0326
#> 5 1 5 8.64 -0.970 0.0974 0.974 8.64
#> 6 1 6 0.00239 -0.539 0.168 0.0237 0.00239
#> 7 1 7 5.16 -0.108 0.235 0.898 5.16
#> 8 1 8 5.95 0.323 0.273 0.925 5.95
#> 9 1 9 3.34 0.754 0.266 0.794 3.34
#> 10 1 10 0.142 1.18 0.222 0.182 0.142
#> # ℹ 40 more rows