
Tidy Randomly Generated Inverse Gamma Distribution Tibble
Source:R/random-tidy-gamma-inverse.R
tidy_inverse_gamma.Rd
This function will generate n
random points from an inverse gamma
distribution with a user provided, .shape
, .rate
, .scale
, 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.
- .shape
Must be strictly positive.
- .rate
An alternative way to specify the
.scale
- .scale
Must be strictly positive.
- .num_sims
The number of randomly generated simulations you want.
Details
This function uses the underlying actuar::rinvgamma()
, and its underlying
p
, d
, and q
functions. For more information please see actuar::rinvgamma()
See also
https://openacttexts.github.io/Loss-Data-Analytics/ChapSummaryDistributions.html
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_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 Gamma:
tidy_gamma()
,
util_gamma_param_estimate()
,
util_gamma_stats_tbl()
Other Inverse Distribution:
tidy_inverse_burr()
,
tidy_inverse_exponential()
,
tidy_inverse_normal()
,
tidy_inverse_pareto()
,
tidy_inverse_weibull()
Examples
tidy_inverse_gamma()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 0.246 -2.92 0.000831 0.0171 0.246
#> 2 1 2 0.363 -2.18 0.00622 0.0634 0.363
#> 3 1 3 2.10 -1.43 0.0291 0.620 2.10
#> 4 1 4 1.77 -0.685 0.0871 0.568 1.77
#> 5 1 5 0.741 0.0602 0.170 0.260 0.741
#> 6 1 6 0.814 0.806 0.223 0.293 0.814
#> 7 1 7 1.19 1.55 0.204 0.430 1.19
#> 8 1 8 0.928 2.30 0.141 0.341 0.928
#> 9 1 9 1.35 3.04 0.0829 0.476 1.35
#> 10 1 10 0.358 3.79 0.0493 0.0611 0.358
#> # ℹ 40 more rows