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)length(n) > 1, the length is
taken to be the number required.TRUE, probabilities/densities
$p$ are returned as $\log(p)$.TRUE (default), probabilities are
$P[X \le x]$, otherwise, $P[X > x]$.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.
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 $E[X^k]$ and the $k$th limited moment at some limit $d$ is $E[\min(X, d)^k]$.
For numerical evaluation purposes, levinvpareto requires that
-shape < order < 1.
exp(dinvpareto(2, 3, 4, log = TRUE))
p <- (1:10)/10
pinvpareto(qinvpareto(p, 2, 3), 2, 3)
minvpareto(0.5, 1, 2)Run the code above in your browser using DataLab