
Tidy Randomly Generated Chisquare (Non-Central) Distribution Tibble
Source:R/random-tidy-chisquare.R
tidy_chisquare.Rd
This 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_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 (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 3.08 -2.66 0.00143 0.772 3.08
#> 2 1 2 0.0420 -2.40 0.00346 0.0991 0.0420
#> 3 1 3 0.308 -2.13 0.00766 0.268 0.308
#> 4 1 4 4.08 -1.87 0.0156 0.845 4.08
#> 5 1 5 0.0554 -1.61 0.0292 0.114 0.0554
#> 6 1 6 2.69 -1.35 0.0504 0.734 2.69
#> 7 1 7 0.322 -1.09 0.0798 0.274 0.322
#> 8 1 8 4.37 -0.823 0.117 0.861 4.37
#> 9 1 9 5.45 -0.560 0.157 0.908 5.45
#> 10 1 10 0.171 -0.298 0.195 0.200 0.171
#> # ℹ 40 more rows