| Pareto {actuar} | R Documentation |
The Pareto Distribution
Description
Density function, distribution function, quantile function, random generation,
raw moments and limited moments for the Pareto distribution with
parameters shape and scale.
Usage
dpareto(x, shape, scale, log = FALSE)
ppareto(q, shape, scale, lower.tail = TRUE, log.p = FALSE)
qpareto(p, shape, scale, lower.tail = TRUE, log.p = FALSE)
rpareto(n, shape, scale)
mpareto(order, shape, scale)
levpareto(limit, shape, scale, order = 1)
Arguments
x, q |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations. If |
shape, scale |
parameters. Must be strictly positive. |
log, log.p |
logical; if |
lower.tail |
logical; if |
order |
order of the moment. |
limit |
limit of the loss variable. |
Details
The Pareto distribution with parameters shape =
\alpha and scale = \theta has density:
f(x) = \frac{\alpha \theta^\alpha}{(x + \theta)^{\alpha + 1}}
for x > 0, \alpha > 0 and \theta.
There are many different definitions of the Pareto distribution in the literature; see Arnold (2015) or Kleiber and Kotz (2003). In the nomenclature of actuar, The “Pareto distribution” does not have a location parameter. The version with a location parameter is the Pareto II.
The kth raw moment of the random variable X is
E[X^k], -1 < k < \alpha.
The kth limited moment at some limit
d is E[\min(X, d)^k],
k > -1 and \alpha - k not a
negative integer.
Value
dpareto gives the density,
ppareto gives the distribution function,
qpareto gives the quantile function,
rpareto generates random deviates,
mpareto gives the kth raw moment, and
levpareto gives the kth moment of the limited loss variable.
Invalid arguments will result in return value NaN, with a warning.
Note
levpareto computes the limited expected value using
betaint.
The version of the Pareto defined for x > \theta is named
Single Parameter Pareto, or Pareto I, in actuar.
Author(s)
Vincent Goulet vincent.goulet@act.ulaval.ca and Mathieu Pigeon
References
Kleiber, C. and Kotz, S. (2003), Statistical Size Distributions in Economics and Actuarial Sciences, Wiley.
Klugman, S. A., Panjer, H. H. and Willmot, G. E. (2012), Loss Models, From Data to Decisions, Fourth Edition, Wiley.
See Also
dpareto2 for an equivalent distribution with location
parameter.
dpareto1 for the Single Parameter Pareto distribution.
"distributions" package vignette for details on the
interrelations between the continuous size distributions in
actuar and complete formulas underlying the above functions.
Examples
exp(dpareto(2, 3, 4, log = TRUE))
p <- (1:10)/10
ppareto(qpareto(p, 2, 3), 2, 3)
## variance
mpareto(2, 4, 1) - mpareto(1, 4, 1)^2
## case with shape - order > 0
levpareto(10, 3, scale = 1, order = 2)
## case with shape - order < 0
levpareto(10, 1.5, scale = 1, order = 2)