This function will generate n
random points from a rf
distribution with a user provided, df1
,df2
, and 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.
- .df1
Degrees of freedom, Inf is allowed.
- .df2
Degrees of freedom, Inf is allowed.
- .ncp
Non-centrality parameter.
- .num_sims
The number of randomly generated simulations you want.
- .return_tibble
A logical value indicating whether to return the result as a tibble. Default is TRUE.
Details
This function uses the underlying stats::rf()
, and its underlying
p
, d
, and q
functions. For more information please see stats::rf()
See also
https://www.itl.nist.gov/div898/handbook/eda/section3/eda3665.htm
Other Continuous Distribution:
tidy_beta()
,
tidy_burr()
,
tidy_cauchy()
,
tidy_chisquare()
,
tidy_exponential()
,
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_pareto()
,
tidy_pareto1()
,
tidy_t()
,
tidy_triangular()
,
tidy_uniform()
,
tidy_weibull()
,
tidy_zero_truncated_geometric()
Other F Distribution:
util_f_stats_tbl()
Examples
tidy_f()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 4.66 -4.09 0.00124 0.724 4.66
#> 2 1 2 0.107 -0.794 0.120 0.201 0.107
#> 3 1 3 3.22 2.50 0.0981 0.676 3.22
#> 4 1 4 0.159 5.79 0.0151 0.242 0.159
#> 5 1 5 0.00313 9.08 0.00921 0.0356 0.00313
#> 6 1 6 0.181 12.4 0.00443 0.256 0.181
#> 7 1 7 14.7 15.7 0.0104 0.838 14.7
#> 8 1 8 0.762 19.0 0.000345 0.457 0.762
#> 9 1 9 107. 22.3 0.00320 0.939 107.
#> 10 1 10 0.167 25.5 0.00867 0.247 0.167
#> # ℹ 40 more rows