This function will generate n random points from a cauchy
distribution with a user provided, .location, .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_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.
- .location
The location parameter.
- .scale
The scale parameter, must be greater than or equal to 0.
- .num_sims
The number of randomly generated simulations you want.
Details
This function uses the underlying stats::rcauchy(), and its underlying
p, d, and q functions. For more information please see stats::rcauchy()
See also
https://www.itl.nist.gov/div898/handbook/eda/section3/eda3663.htm
Other Continuous Distribution:
tidy_beta(),
tidy_burr(),
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_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 Cauchy:
util_cauchy_param_estimate(),
util_cauchy_stats_tbl()
Examples
tidy_cauchy()
#> # A tibble: 50 × 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 1.21 -306. 4.40e- 4 0.780 1.21
#> 2 1 2 0.565 -299. 8.08e-14 0.664 0.565
#> 3 1 3 -2.25 -291. 0 0.133 -2.25
#> 4 1 4 0.468 -283. 2.54e-18 0.639 0.468
#> 5 1 5 -0.426 -275. 8.05e-19 0.372 -0.426
#> 6 1 6 -3.07 -268. 3.77e-20 0.100 -3.07
#> 7 1 7 42.0 -260. 5.72e-19 0.992 42.0
#> 8 1 8 -2.96 -252. 1.39e-18 0.104 -2.96
#> 9 1 9 0.442 -245. 0 0.632 0.442
#> 10 1 10 -0.964 -237. 1.72e-19 0.256 -0.964
#> # ℹ 40 more rows
