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 0.279 -0.341 0.00299 0.279 0.279
#> 2 1 2 0.393 -0.307 0.00729 0.393 0.393
#> 3 1 3 0.845 -0.273 0.0164 0.845 0.845
#> 4 1 4 0.237 -0.239 0.0339 0.237 0.237
#> 5 1 5 0.494 -0.205 0.0647 0.494 0.494
#> 6 1 6 0.357 -0.171 0.114 0.357 0.357
#> 7 1 7 0.860 -0.137 0.186 0.860 0.860
#> 8 1 8 0.892 -0.104 0.283 0.892 0.892
#> 9 1 9 0.0792 -0.0696 0.400 0.0792 0.0792
#> 10 1 10 0.170 -0.0357 0.530 0.170 0.170
#> # ℹ 40 more rows