Exponential
The Exponential Distribution
Description
Calculates density, cumulative probability, quantile, and
generate random sample for the exponential distribution (continuous).
Usage
dexp(x, rate = 1, log = FALSE) # density
pexp(q, rate = 1, lower.tail = TRUE, log.p = FALSE) # probability
qexp(p, rate = 1, lower.tail = TRUE, log.p = FALSE) # quantile
rexp(n, rate = 1) # random
Arguments
| x, q |
numeric vectors in the range [0, 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.
|
| rate |
a numeric vector in the range [0, Inf) that specifies the rate 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 (dexp),
cumulative probability (pexp),
quantile (qexp), or
random sample (rexp)
for the exponential distribution with parameter rate.
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 exponential distributions is a family of continuous probability distributions
defined on the interval [0, Inf) and parameterized by a positive parameter rate.
References
Johnson, N. L. and Kotz, S. (1970).
Continuous Univariate Distributions, vol. 1 and 2.
Houghton-Mifflin, Boston.
See Also
Examples
dexp(seq(0.0001, 6, length = 20))