Density function, distribution function, quantile function, random generation
raw moments and limited moments for the Inverse Exponential
distribution with parameter scale
.
dinvexp(x, rate = 1, scale = 1/rate, log = FALSE)
pinvexp(q, rate = 1, scale = 1/rate, lower.tail = TRUE, log.p = FALSE)
qinvexp(p, rate = 1, scale = 1/rate, lower.tail = TRUE, log.p = FALSE)
rinvexp(n, rate = 1, scale = 1/rate)
minvexp(order, rate = 1, scale = 1/rate)
levinvexp(limit, rate = 1, scale = 1/rate, order)
dinvexp
gives the density,
pinvexp
gives the distribution function,
qinvexp
gives the quantile function,
rinvexp
generates random deviates,
minvexp
gives the \(k\)th raw moment, and
levinvexp
calculates the \(k\)th limited moment.
Invalid arguments will result in return value NaN
, with a warning.
vector of quantiles.
vector of probabilities.
number of observations. If length(n) > 1
, the length is
taken to be the number required.
parameter. Must be strictly positive.
an alternative way to specify the scale.
logical; if TRUE
, probabilities/densities
\(p\) are returned as \(\log(p)\).
logical; if TRUE
(default), probabilities are
\(P[X \le x]\), otherwise, \(P[X > x]\).
order of the moment.
limit of the loss variable.
Vincent Goulet vincent.goulet@act.ulaval.ca and Mathieu Pigeon
The inverse exponential distribution with parameter scale
\(= \theta\) has density:
$$f(x) = \frac{\theta e^{-\theta/x}}{x^2}$$
for \(x > 0\) and \(\theta > 0\).
The \(k\)th raw moment of the random variable \(X\) is \(E[X^k]\), \(k < 1\), and the \(k\)th limited moment at some limit \(d\) is \(E[\min(X, d)^k]\), all \(k\).
Klugman, S. A., Panjer, H. H. and Willmot, G. E. (2012), Loss Models, From Data to Decisions, Fourth Edition, Wiley.
exp(dinvexp(2, 2, log = TRUE))
p <- (1:10)/10
pinvexp(qinvexp(p, 2), 2)
minvexp(0.5, 2)
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