This function will generate n
random points from a logistic
distribution with a user provided, .location
, .scale
, 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_logistic(
.n = 50,
.location = 0,
.scale = 1,
.num_sims = 1,
.return_tibble = TRUE
)
A tibble of randomly generated data.
The number of randomly generated points you want.
The location parameter
The scale parameter
The number of randomly generated simulations you want.
A logical value indicating whether to return the result as a tibble. Default is TRUE.
Steven P. Sanderson II, MPH
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 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_lognormal()
,
tidy_normal()
,
tidy_paralogistic()
,
tidy_pareto()
,
tidy_pareto1()
,
tidy_t()
,
tidy_triangular()
,
tidy_uniform()
,
tidy_weibull()
,
tidy_zero_truncated_geometric()
Other Logistic:
tidy_paralogistic()
,
util_logistic_param_estimate()
,
util_logistic_stats_tbl()