Tidy Randomly Generated Inverse Exponential Distribution Tibble
Source:R/random-tidy-exponential-inverse.R
tidy_inverse_exponential.Rd
This function will generate n
random points from an inverse exponential
distribution with a user provided, .rate
or .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.
- .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::rinvexp()
, and its underlying
p
, d
, and q
functions. For more information please see actuar::rinvexp()
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_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 Exponential:
tidy_exponential()
,
util_exponential_param_estimate()
,
util_exponential_stats_tbl()
Other Inverse Distribution:
tidy_inverse_burr()
,
tidy_inverse_gamma()
,
tidy_inverse_normal()
,
tidy_inverse_pareto()
,
tidy_inverse_weibull()
Examples
tidy_inverse_exponential()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 3.36 -1.62 0.000695 0.742 3.36
#> 2 1 2 1.08 -1.19 0.00594 0.396 1.08
#> 3 1 3 0.832 -0.759 0.0314 0.301 0.832
#> 4 1 4 4.43 -0.328 0.105 0.798 4.43
#> 5 1 5 1.03 0.103 0.228 0.380 1.03
#> 6 1 6 0.382 0.534 0.337 0.0728 0.382
#> 7 1 7 11.1 0.965 0.362 0.914 11.1
#> 8 1 8 0.744 1.40 0.299 0.261 0.744
#> 9 1 9 3.85 1.83 0.200 0.771 3.85
#> 10 1 10 1.37 2.26 0.123 0.482 1.37
#> # … with 40 more rows