This function will generate n
random points from a paralogistic
distribution with a user provided, .shape
, .rate
, .scale
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 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_paralogistic(
.n = 50,
.shape = 1,
.rate = 1,
.scale = 1/.rate,
.num_sims = 1,
.return_tibble = TRUE
)
A tibble of randomly generated data.
The number of randomly generated points you want.
Must be strictly positive.
An alternative way to specify the .scale
Must be strictly positive.
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 actuar::rparalogis()
, and its underlying
p
, d
, and q
functions. For more information please see actuar::rparalogis()
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_logistic()
,
tidy_lognormal()
,
tidy_normal()
,
tidy_pareto()
,
tidy_pareto1()
,
tidy_t()
,
tidy_triangular()
,
tidy_uniform()
,
tidy_weibull()
,
tidy_zero_truncated_geometric()
Other Logistic:
tidy_logistic()
,
util_logistic_param_estimate()
,
util_logistic_stats_tbl()