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.
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_pareto1()
,
tidy_pareto()
,
tidy_t()
,
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 0.0666 -0.324 0.00267 0.0666 0.0666
#> 2 1 2 0.371 -0.291 0.00636 0.371 0.371
#> 3 1 3 0.746 -0.257 0.0140 0.746 0.746
#> 4 1 4 0.630 -0.223 0.0286 0.630 0.630
#> 5 1 5 0.407 -0.189 0.0540 0.407 0.407
#> 6 1 6 0.0278 -0.156 0.0945 0.0278 0.0278
#> 7 1 7 0.200 -0.122 0.153 0.200 0.200
#> 8 1 8 0.555 -0.0882 0.230 0.555 0.555
#> 9 1 9 0.567 -0.0545 0.322 0.567 0.567
#> 10 1 10 0.239 -0.0208 0.421 0.239 0.239
#> # … with 40 more rows