Pareto3 | R Documentation |
Density function, distribution function, quantile function, random generation,
raw moments and limited moments for the Pareto III distribution with
parameters min
, shape
and scale
.
dpareto3(x, min, shape, rate = 1, scale = 1/rate,
log = FALSE)
ppareto3(q, min, shape, rate = 1, scale = 1/rate,
lower.tail = TRUE, log.p = FALSE)
qpareto3(p, min, shape, rate = 1, scale = 1/rate,
lower.tail = TRUE, log.p = FALSE)
rpareto3(n, min, shape, rate = 1, scale = 1/rate)
mpareto3(order, min, shape, rate = 1, scale = 1/rate)
levpareto3(limit, min, shape, rate = 1, scale = 1/rate,
order = 1)
x, q |
vector of quantiles. |
p |
vector of probabilities. |
n |
number of observations. If |
min |
lower bound of the support of the distribution. |
shape, 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. |
The Pareto III (or “type III”) distribution with parameters
min
= \mu
,
shape
= \gamma
and
scale
= \theta
has density:
f(x) = \frac{\gamma ((x - \mu)/\theta)^{\gamma - 1}}{%
\theta [1 + ((x - \mu)/\theta)^\gamma]^2}
for x > \mu
, -\infty < \mu < \infty
,
\gamma > 0
and \theta > 0
.
The Pareto III is the distribution of the random variable
\mu + \theta \left(\frac{X}{1 - X}\right)^{1/\gamma},
where X
has a uniform distribution on (0, 1)
. It derives
from the Feller-Pareto
distribution with \alpha = \tau = 1
.
Setting \mu = 0
yields the loglogistic
distribution.
The k
th raw moment of the random variable X
is
E[X^k]
for nonnegative integer values of k <
\gamma
.
The k
th limited moment at some limit d
is E[\min(X,
d)^k]
for nonnegative integer values of k
and 1 - j/\gamma
, j = 1, \dots, k
not a negative integer.
dpareto3
gives the density,
ppareto3
gives the distribution function,
qpareto3
gives the quantile function,
rpareto3
generates random deviates,
mpareto3
gives the k
th raw moment, and
levpareto3
gives the k
th moment of the limited loss
variable.
Invalid arguments will result in return value NaN
, with a warning.
levpareto3
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.
Vincent Goulet vincent.goulet@act.ulaval.ca
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.
dllogis
for the loglogistic distribution.
exp(dpareto3(1, min = 10, 3, 4, log = TRUE))
p <- (1:10)/10
ppareto3(qpareto3(p, min = 10, 2, 3), min = 10, 2, 3)
## mean
mpareto3(1, min = 10, 2, 3)
## case with 1 - order/shape > 0
levpareto3(20, min = 10, 2, 3, order = 1)
## case with 1 - order/shape < 0
levpareto3(20, min = 10, 2/3, 3, order = 1)
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