invexp {invgamma} | R Documentation |
The Inverse Exponential Distribution
Description
Density, distribution function, quantile function and random generation for the inverse exponential distribution.
Usage
dinvexp(x, rate = 1, log = FALSE)
pinvexp(q, rate = 1, lower.tail = TRUE, log.p = FALSE)
qinvexp(p, rate = 1, lower.tail = TRUE, log.p = FALSE)
rinvexp(n, rate = 1)
Arguments
x , q |
vector of quantiles. |
rate |
degrees of freedom (non-negative, but can be non-integer). |
log , log.p |
logical; if TRUE, probabilities p are given as log(p). |
lower.tail |
logical; if TRUE (default), probabilities are P[X <= x] otherwise, P[X > x]. |
p |
vector of probabilities. |
n |
number of observations. If length(n) > 1, the length is taken to be the number required. |
Details
The functions (d/p/q/r)invexp simply wrap those of the standard
(d/p/q/r)exp R implementation, so look at, say,
dexp
for details.
See Also
dexp
; these functions just wrap the
(d/p/q/r)exp functions.
Examples
s <- seq(0, 10, .01)
plot(s, dinvexp(s, 2), type = 'l')
f <- function(x) dinvexp(x, 2)
q <- 3
integrate(f, 0, q)
(p <- pinvexp(q, 2))
qinvexp(p, 2) # = q
mean(rinvexp(1e5, 2) <= q)
pinvgamma(q, 1, 2)
[Package invgamma version 1.1 Index]