SingleParameterPareto {actuar}R Documentation

The Single-parameter Pareto Distribution

Description

Density function, distribution function, quantile function, random generation, raw moments, and limited moments for the Single-parameter Pareto distribution with parameter shape.

Usage

dpareto1(x, shape, min, log = FALSE)
ppareto1(q, shape, min, lower.tail = TRUE, log.p = FALSE)
qpareto1(p, shape, min, lower.tail = TRUE, log.p = FALSE)
rpareto1(n, shape, min)
mpareto1(order, shape, min)
levpareto1(limit, shape, min, order = 1)

Arguments

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

parameter. Must be strictly positive.

min

lower bound of the support of the distribution.

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.

Details

The single-parameter Pareto, or Pareto I, distribution with parameter shape = a has density:

f(x) = a b^a/x^(a + 1)

for x > b, a > 0 and b > 0.

Although there appears to be two parameters, only shape is a true parameter. The value of min = b must be set in advance.

The kth raw moment of the random variable X is E[X^k], k < shape and the kth limited moment at some limit d is E[min(X, d)^k], x ≥ min.

Value

dpareto1 gives the density, ppareto1 gives the distribution function, qpareto1 gives the quantile function, rpareto1 generates random deviates, mpareto1 gives the kth raw moment, and levpareto1 gives the kth moment of the limited loss variable.

Invalid arguments will result in return value NaN, with a warning.

Note

For Pareto distributions, we use the classification of Arnold (2015) with the parametrization of Klugman et al. (2012).

The "distributions" package vignette provides the interrelations between the continuous size distributions in actuar and the complete formulas underlying the above functions.

Author(s)

Vincent Goulet vincent.goulet@act.ulaval.ca and Mathieu Pigeon

References

Arnold, B.C. (2015), Pareto Distributions, Second Edition, CRC Press.

Klugman, S. A., Panjer, H. H. and Willmot, G. E. (2012), Loss Models, From Data to Decisions, Fourth Edition, Wiley.

See Also

dpareto for the two-parameter Pareto distribution.

Examples

exp(dpareto1(5, 3, 4, log = TRUE))
p <- (1:10)/10
ppareto1(qpareto1(p, 2, 3), 2, 3)
mpareto1(2, 3, 4) - mpareto(1, 3, 4) ^ 2
levpareto(10, 3, 4, order = 2)

[Package actuar version 3.1-4 Index]