This function will generate n
random points from a logisitc
distribution with a user provided, rate, and number of
random simulations to be produced. The function returns a tibble with the
simulation number column the x column which corresonds 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_logisitc(.n = 50, .location = 0, .scale = 1, .num_sims = 1)
The number of randomly generated points you want.
The location parameter
The scale parameter
The number of randomly generated simulations you want.
A tibble of randomly generated data.
This function uses the underlying stats::rlogis()
, and its underlying
p
, d
, and q
functions. For more information please see stats::rlogis()
https://en.wikipedia.org/wiki/Logistic_distribution
Other Data Generator:
tidy_beta()
,
tidy_exponential()
,
tidy_gamma()
,
tidy_lognormal()
,
tidy_normal()
,
tidy_poisson()
,
tidy_uniform()
,
tidy_weibull()
tidy_logisitc()
#> # A tibble: 50 x 7
#> sim_number x y dx dy p q
#> <fct> <int> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 1 1 1.58 -6.47 0.000148 1.93e-22 -Inf
#> 2 1 2 -1.94 -6.20 0.000500 1.43e-21 -3.87
#> 3 1 3 -1.94 -5.94 0.00140 1.05e-20 -3.16
#> 4 1 4 -0.579 -5.67 0.00330 7.78e-20 -2.73
#> 5 1 5 -0.376 -5.41 0.00657 5.75e-19 -2.42
#> 6 1 6 1.00 -5.14 0.0112 4.25e-18 -2.17
#> 7 1 7 -0.451 -4.88 0.0169 3.14e-17 -1.97
#> 8 1 8 -0.190 -4.61 0.0227 2.32e-16 -1.79
#> 9 1 9 0.108 -4.35 0.0279 1.71e-15 -1.63
#> 10 1 10 0.645 -4.08 0.0312 1.27e-14 -1.49
#> # ... with 40 more rows