Density function, distribution function, quantile function, random generation
raw moments and limited moments for the Inverse Pareto distribution
with parameters shape
and scale
.
dinvpareto(x, shape, scale, log = FALSE)
pinvpareto(q, shape, scale, lower.tail = TRUE, log.p = FALSE)
qinvpareto(p, shape, scale, lower.tail = TRUE, log.p = FALSE)
rinvpareto(n, shape, scale)
minvpareto(order, shape, scale)
levinvpareto(limit, shape, scale, order = 1)
dinvpareto
gives the density,
pinvpareto
gives the distribution function,
qinvpareto
gives the quantile function,
rinvpareto
generates random deviates,
minvpareto
gives the \(k\)th raw moment, and
levinvpareto
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.
parameters. Must be strictly positive.
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 Pareto distribution with parameters shape
\(=
\tau\) and scale
\(= \theta\) has density:
$$f(x) = \frac{\tau \theta x^{\tau - 1}}{%
(x + \theta)^{\tau + 1}}$$
for \(x > 0\), \(\tau > 0\) and \(\theta > 0\).
The \(k\)th raw moment of the random variable \(X\) is \(E[X^k]\), \(-\tau < k < 1\).
The \(k\)th limited moment at some limit \(d\) is \(E[\min(X, d)^k]\), \(k > -\tau\).
Klugman, S. A., Panjer, H. H. and Willmot, G. E. (2012), Loss Models, From Data to Decisions, Fourth Edition, Wiley.
exp(dinvpareto(2, 3, 4, log = TRUE))
p <- (1:10)/10
pinvpareto(qinvpareto(p, 2, 3), 2, 3)
minvpareto(0.5, 1, 2)
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