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 ofn
for the current simulation.y
The randomly generated data point.dx
Thex
value from thestats::density()
function.dy
They
value from thestats::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.
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.
Details
This function uses the underlying stats::runif()
, and its underlying
p
, d
, and q
functions. For more information please see stats::runif()
See also
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()
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 0.0624 -0.378 0.00158 0.0624 0.0624
#> 2 1 2 0.725 -0.342 0.00387 0.725 0.725
#> 3 1 3 0.719 -0.306 0.00881 0.719 0.719
#> 4 1 4 0.841 -0.270 0.0186 0.841 0.841
#> 5 1 5 0.375 -0.235 0.0367 0.375 0.375
#> 6 1 6 0.668 -0.199 0.0674 0.668 0.668
#> 7 1 7 0.821 -0.163 0.115 0.821 0.821
#> 8 1 8 0.283 -0.127 0.184 0.283 0.283
#> 9 1 9 0.993 -0.0916 0.275 0.993 0.993
#> 10 1 10 0.271 -0.0559 0.385 0.271 0.271
#> # ℹ 40 more rows