
Tidy Randomly Generated Exponential Distribution Tibble
Source:R/random-tidy-exponential.R
tidy_exponential.RdThis function will generate n random points from a exponential
distribution with a user provided, .rate, 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_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.
Arguments
- .n
The number of randomly generated points you want.
- .rate
A vector of rates
- .num_sims
The number of randomly generated simulations you want.
Details
This function uses the underlying stats::rexp(), and its underlying
p, d, and q functions. For more information please see stats::rexp()
See also
https://www.itl.nist.gov/div898/handbook/eda/section3/eda3667.htm
Other Continuous Distribution:
tidy_beta(),
tidy_burr(),
tidy_cauchy(),
tidy_chisquare(),
tidy_f(),
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_pareto1(),
tidy_pareto(),
tidy_t(),
tidy_uniform(),
tidy_weibull(),
tidy_zero_truncated_geometric()
Other Exponential:
tidy_inverse_exponential(),
util_exponential_param_estimate(),
util_exponential_stats_tbl()
Examples
tidy_exponential()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 0.190 -0.606 0.00139 0.173 0.190
#> 2 1 2 0.140 -0.478 0.00804 0.130 0.140
#> 3 1 3 0.189 -0.349 0.0345 0.172 0.189
#> 4 1 4 0.690 -0.221 0.111 0.499 0.690
#> 5 1 5 0.393 -0.0927 0.268 0.325 0.393
#> 6 1 6 1.10 0.0357 0.500 0.668 1.10
#> 7 1 7 1.62 0.164 0.733 0.802 1.62
#> 8 1 8 0.428 0.292 0.869 0.348 0.428
#> 9 1 9 0.294 0.421 0.864 0.254 0.294
#> 10 1 10 0.657 0.549 0.754 0.481 0.657
#> # ℹ 40 more rows