Logistic {distributions3} | R Documentation |
Create a Logistic distribution
Description
A continuous distribution on the real line. For binary outcomes
the model given by where
is the Logistic
cdf()
is called logistic regression.
Usage
Logistic(location = 0, scale = 1)
Arguments
location |
The location parameter for the distribution. For Logistic distributions, the location parameter is the mean, median and also mode. Defaults to zero. |
scale |
The scale parameter for the distribution. Defaults to one. |
Details
We recommend reading this documentation on https://alexpghayes.github.io/distributions3/, where the math will render with additional detail and much greater clarity.
In the following, let be a Logistic random variable with
location
= and
scale
= .
Support: , the set of all real numbers
Mean:
Variance:
Probability density function (p.d.f):
Cumulative distribution function (c.d.f):
Moment generating function (m.g.f):
where is the Beta function.
Value
A Logistic
object.
See Also
Other continuous distributions:
Beta()
,
Cauchy()
,
ChiSquare()
,
Erlang()
,
Exponential()
,
FisherF()
,
Frechet()
,
GEV()
,
GP()
,
Gamma()
,
Gumbel()
,
LogNormal()
,
Normal()
,
RevWeibull()
,
StudentsT()
,
Tukey()
,
Uniform()
,
Weibull()
Examples
set.seed(27)
X <- Logistic(2, 4)
X
random(X, 10)
pdf(X, 2)
log_pdf(X, 2)
cdf(X, 4)
quantile(X, 0.7)