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_number The current simulation number.
x The current value of n for the current simulation.
y The randomly generated data point.
dx The x value from the stats::density() function.
dy The y value from the stats::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.
tidy_cauchy(
.n = 50,
.location = 0,
.scale = 1,
.num_sims = 1,
.return_tibble = TRUE
)A tibble of randomly generated data.
The number of randomly generated points you want.
The location parameter.
The scale parameter, must be greater than or equal to 0.
The number of randomly generated simulations you want.
A logical value indicating whether to return the result as a tibble. Default is TRUE.
Steven P. Sanderson II, MPH
This function uses the underlying stats::rcauchy(), and its underlying
p, d, and q functions. For more information please see stats::rcauchy()
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_pareto(),
tidy_pareto1(),
tidy_t(),
tidy_triangular(),
tidy_uniform(),
tidy_weibull(),
tidy_zero_truncated_geometric()
Other Cauchy:
util_cauchy_param_estimate(),
util_cauchy_stats_tbl()