| InversePareto {actuar} | R Documentation | 
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)
x, q | 
vector of quantiles. | 
p | 
vector of probabilities. | 
n | 
number of observations. If length(n) > 1, the length is
taken to be the number required. | 
shape, scale | 
parameters. Must be strictly positive. | 
log, log.p | 
logical; if TRUE, probabilities/densities
p are returned as log(p). | 
lower.tail | 
logical; if TRUE (default), probabilities are
P[X <= x], otherwise, P[X > x]. | 
order | 
order of the moment. | 
limit | 
limit of the loss variable. | 
The Inverse Pareto distribution with parameters shape = a and scale = s has density:
f(x) = a s x^(a - 1)/(x + s)^(a + 1)
for x > 0, a > 0 and s > 0.
The kth raw moment of the random variable X is E[X^k] and the kth limited moment at some limit d is E[min(X, d)^k].
Evaluation of levinvpareto is done using numerical integration.
dinvpareto gives the density,
pinvpareto gives the distribution function,
qinvpareto gives the quantile function,
rinvpareto generates random deviates,
minvpareto gives the kth raw moment, and
levinvpareto calculates the kth limited moment.
Invalid arguments will result in return value NaN, with a warning.
Vincent Goulet vincent.goulet@act.ulaval.ca and Mathieu Pigeon
Klugman, S. A., Panjer, H. H. and Willmot, G. E. (2004), Loss Models, From Data to Decisions, Second 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)