
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 1.32 -2.31 0.00139 0.544 1.32
#> 2 1 2 2.16 -2.07 0.00358 0.674 2.16
#> 3 1 3 2.56 -1.83 0.00839 0.721 2.56
#> 4 1 4 0.225 -1.59 0.0179 0.229 0.225
#> 5 1 5 1.67 -1.35 0.0348 0.604 1.67
#> 6 1 6 0.705 -1.11 0.0616 0.403 0.705
#> 7 1 7 2.85 -0.865 0.0997 0.750 2.85
#> 8 1 8 5.89 -0.624 0.147 0.923 5.89
#> 9 1 9 0.428 -0.382 0.199 0.316 0.428
#> 10 1 10 0.627 -0.141 0.246 0.381 0.627
#> # ℹ 40 more rows