Tidy Randomly Generated Uniform Distribution Tibble

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.

Usage

tidy_uniform(.n = 50, .min = 0, .max = 1, .num_sims = 1, .return_tibble = TRUE)

Arguments

.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.

Value

A tibble of randomly generated data.

Details

This function uses the underlying stats::runif(), and its underlying p, d, and q functions. For more information please see stats::runif()

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()

Author

Steven P. Sanderson II, MPH

Examples

tidy_uniform()
#> # A tibble: 50 × 7
#>    sim_number     x     y      dx      dy     p     q
#>    <fct>      <int> <dbl>   <dbl>   <dbl> <dbl> <dbl>
#>  1 1              1 0.104 -0.345  0.00179 0.104 0.104
#>  2 1              2 0.399 -0.310  0.00427 0.399 0.399
#>  3 1              3 0.561 -0.276  0.00941 0.561 0.561
#>  4 1              4 0.568 -0.242  0.0191  0.568 0.568
#>  5 1              5 0.189 -0.208  0.0361  0.189 0.189
#>  6 1              6 0.533 -0.173  0.0633  0.533 0.533
#>  7 1              7 0.446 -0.139  0.104   0.446 0.446
#>  8 1              8 0.174 -0.105  0.159   0.174 0.174
#>  9 1              9 0.822 -0.0709 0.232   0.822 0.822
#> 10 1             10 0.801 -0.0367 0.322   0.801 0.801
#> # ℹ 40 more rows