View source: R/random-tidy-uniform.R
| tidy_uniform | R Documentation |
This function will generate n random points from a uniform
distribution with a user provided, .min and .max values, 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_uniform(.n = 50, .min = 0, .max = 1, .num_sims = 1, .return_tibble = TRUE)
.n |
The number of randomly generated points you want. |
.min |
A lower limit of the distribution. |
.max |
An upper limit of the distribution |
.num_sims |
The number of randomly generated simulations you want. |
.return_tibble |
A logical value indicating whether to return the result as a tibble. Default is TRUE. |
This function uses the underlying stats::runif(), and its underlying
p, d, and q functions. For more information please see stats::runif()
A tibble of randomly generated data.
Steven P. Sanderson II, MPH
https://www.itl.nist.gov/div898/handbook/eda/section3/eda3662.htm
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_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_weibull(),
tidy_zero_truncated_geometric()
Other Uniform:
util_uniform_param_estimate(),
util_uniform_stats_tbl()
tidy_uniform()
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