
Tidy Randomly Generated Inverse Gaussian Distribution Tibble
Source:R/random-tidy-normal-inverse.R
tidy_inverse_normal.Rd
This function will generate n
random points from an Inverse Gaussian
distribution with a user provided, .mean
, .shape
, .dispersion
The function
returns a tibble with the simulation number column the x column which corresponds
to the n randomly generated points.
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.
- .mean
Must be strictly positive.
- .shape
Must be strictly positive.
- .dispersion
An alternative way to specify the
.shape
.- .num_sims
The number of randomly generated simulations you want.
Details
This function uses the underlying actuar::rinvgauss()
. For
more information please see rinvgauss()
See also
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_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 Gaussian:
tidy_normal()
,
util_normal_param_estimate()
,
util_normal_stats_tbl()
Other Inverse Distribution:
tidy_inverse_burr()
,
tidy_inverse_exponential()
,
tidy_inverse_gamma()
,
tidy_inverse_pareto()
,
tidy_inverse_weibull()
Examples
tidy_inverse_normal()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 0.340 -0.300 0.00273 0.208 0.340
#> 2 1 2 0.577 -0.187 0.0220 0.429 0.577
#> 3 1 3 0.165 -0.0734 0.109 0.0352 0.165
#> 4 1 4 0.961 0.0399 0.345 0.652 0.961
#> 5 1 5 0.614 0.153 0.716 0.457 0.614
#> 6 1 6 0.635 0.266 1.04 0.472 0.635
#> 7 1 7 0.560 0.380 1.15 0.416 0.560
#> 8 1 8 1.09 0.493 1.09 0.701 1.09
#> 9 1 9 4.17 0.606 0.924 0.982 4.17
#> 10 1 10 4.79 0.720 0.724 0.988 4.79
#> # ℹ 40 more rows