Logistic
The Logistic Distribution
Description
Calculates density, cumulative probability, quantile, and
generates random sample for the logistic distribution (continuous).
Usage
dlogis(x, location = 0, scale = 1, log = FALSE) # density
plogis(q, location = 0, scale = 1, lower.tail = TRUE, log.p = FALSE) # probability
qlogis(p, location = 0, scale = 1, lower.tail = TRUE, log.p = FALSE) # quantile
rlogis(n, location = 0, scale = 1) # random
Arguments
| x, q |
numeric vectors in the range (-Inf, Inf) that specify the quantiles.
|
| p |
a numeric vector in the range [0, 1] that specifies the probabilities.
|
| n |
an integer scalar in the range [0, Inf) that specifies the number of random samples requested.
If the input value is not an integer, it is truncated.
If length(n) is greater than 1,
the random function returns length(n) random samples.
|
| location |
a numeric vector in the range (-Inf, Inf) that specifies the location parameter.
|
| scale |
a numeric vector in the range [0, Inf) that specifies the scale parameter.
|
| log |
a logical value.
If FALSE (default), the density function returns the density itself.
If TRUE, it returns the log of the density.
|
| lower.tail |
a logical value.
If TRUE (default), the probability supplied to the quantile function
or returned by the probability function is P[X <= x].
If FALSE, it is P[X > x].
|
| log.p |
a logical value.
If FALSE (default), the probability supplied to the quantile function
or returned by the probability function is the probability itself.
If TRUE, it is the log of the probability.
|
Details
The distribution parameter(s) are replicated cyclically to be the same length as
the input x, q, p, or the number of random samples requested.
Missing values (NAs) in the input or the distribution parameter(s)
will cause the corresponding elements of the result to be missing.
Value
returns density (dlogis),
cumulative probability (plogis),
quantile (qlogis), or
random sample (rlogis)
for the logistic distribution with parameters location and scale.
Side Effects
If the .Random.seed dataset exists, the random sample function updates its value.
The random sample function creates the .Random.seed dataset if it does not exist.
Background
The logistic distribution is a family of continuous probability distributions
defined on the interval (-Inf, Inf) and parameterized by two parameters,
location and scale.
References
Johnson, N. L. and Kotz, S. (1970).
Continuous Univariate Distributions, vol. 2.
Houghton-Mifflin, Boston.
Logistic Distribution. In
Encyclopedia of Statistical Sciences.
S. Kotz and N. L. Johnson, eds.
See Also
Examples
dlogis(seq(-6, 6, by = 1))