
Tidy Randomly Generated Inverse Gaussian Distribution Tibble
Source:R/random-tidy-normal-inverse.R
tidy_inverse_normal.RdThis function will generate n random points from an Inverse Gaussian
distribution with a user provided, .mean, .shape, .dispersionThe 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_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.
Usage
tidy_inverse_normal(
.n = 50,
.mean = 1,
.shape = 1,
.dispersion = 1/.shape,
.num_sims = 1,
.return_tibble = TRUE
)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.
- .return_tibble
A logical value indicating whether to return the result as a tibble. Default is TRUE.
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_pareto(),
tidy_pareto1(),
tidy_t(),
tidy_triangular(),
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 0.511 -0.780 0.000677 0.375 0.511
#> 2 1 2 0.572 -0.630 0.00312 0.425 0.572
#> 3 1 3 0.982 -0.481 0.0116 0.661 0.982
#> 4 1 4 0.556 -0.332 0.0355 0.412 0.556
#> 5 1 5 2.95 -0.183 0.0894 0.951 2.95
#> 6 1 6 0.225 -0.0338 0.187 0.0876 0.225
#> 7 1 7 0.862 0.115 0.329 0.607 0.862
#> 8 1 8 0.471 0.265 0.488 0.339 0.471
#> 9 1 9 0.590 0.414 0.618 0.439 0.590
#> 10 1 10 1.26 0.563 0.675 0.754 1.26
#> # ℹ 40 more rows