Pareto4 {actuar} | R Documentation |
The Pareto IV Distribution
Description
Density function, distribution function, quantile function, random generation,
raw moments and limited moments for the Pareto IV distribution with
parameters min
, shape1
, shape2
and scale
.
Usage
dpareto4(x, min, shape1, shape2, rate = 1, scale = 1/rate,
log = FALSE)
ppareto4(q, min, shape1, shape2, rate = 1, scale = 1/rate,
lower.tail = TRUE, log.p = FALSE)
qpareto4(p, min, shape1, shape2, rate = 1, scale = 1/rate,
lower.tail = TRUE, log.p = FALSE)
rpareto4(n, min, shape1, shape2, rate = 1, scale = 1/rate)
mpareto4(order, min, shape1, shape2, rate = 1, scale = 1/rate)
levpareto4(limit, min, shape1, shape2, rate = 1, scale = 1/rate,
order = 1)
Arguments
x , q |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations. If |
min |
lower bound of the support of the distribution. |
shape1 , shape2 , scale |
parameters. Must be strictly positive. |
rate |
an alternative way to specify the scale. |
log , log.p |
logical; if |
lower.tail |
logical; if |
order |
order of the moment. |
limit |
limit of the loss variable. |
Details
The Pareto IV (or “type IV”) distribution with parameters
min
,
shape1
,
shape2
and
scale
has density:
for ,
,
,
and
.
The Pareto IV is the distribution of the random variable
where has a beta distribution with parameters
and
. It derives from the Feller-Pareto
distribution with
. Setting
yields the Burr distribution.
The Pareto IV distribution also has the following direct special cases:
A Pareto III distribution when
shape1 == 1
;A Pareto II distribution when
shape1 == 1
.
The th raw moment of the random variable
is
for nonnegative integer values of
.
The th limited moment at some limit
is
for nonnegative integer values of
and
,
not a negative integer.
Value
dpareto4
gives the density,
ppareto4
gives the distribution function,
qpareto4
gives the quantile function,
rpareto4
generates random deviates,
mpareto4
gives the th raw moment, and
levpareto4
gives the th moment of the limited loss
variable.
Invalid arguments will result in return value NaN
, with a warning.
Note
levpareto4
computes the limited expected value using
betaint
.
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
References
Arnold, B.C. (2015), Pareto Distributions, Second Edition, CRC Press.
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
dburr
for the Burr distribution.
Examples
exp(dpareto4(1, min = 10, 2, 3, log = TRUE))
p <- (1:10)/10
ppareto4(qpareto4(p, min = 10, 2, 3, 2), min = 10, 2, 3, 2)
## variance
mpareto4(2, min = 10, 2, 3, 1) - mpareto4(1, min = 10, 2, 3, 1) ^ 2
## case with shape1 - order/shape2 > 0
levpareto4(10, min = 10, 2, 3, 1, order = 2)
## case with shape1 - order/shape2 < 0
levpareto4(10, min = 10, 1.5, 0.5, 1, order = 2)