Density function, distribution function, quantile function, random generation,
raw moments and limited moments for the Transformed Gamma distribution
with parameters shape1
, shape2
and scale
.
dtrgamma(x, shape1, shape2, rate = 1, scale = 1/rate,
log = FALSE)
ptrgamma(q, shape1, shape2, rate = 1, scale = 1/rate,
lower.tail = TRUE, log.p = FALSE)
qtrgamma(p, shape1, shape2, rate = 1, scale = 1/rate,
lower.tail = TRUE, log.p = FALSE)
rtrgamma(n, shape1, shape2, rate = 1, scale = 1/rate)
mtrgamma(order, shape1, shape2, rate = 1, scale = 1/rate)
levtrgamma(limit, shape1, shape2, rate = 1, scale = 1/rate,
order = 1)
dtrgamma
gives the density,
ptrgamma
gives the distribution function,
qtrgamma
gives the quantile function,
rtrgamma
generates random deviates,
mtrgamma
gives the \(k\)th raw moment, and
levtrgamma
gives the \(k\)th moment of the limited loss
variable.
Invalid arguments will result in return value NaN
, with a warning.
vector of quantiles.
vector of probabilities.
number of observations. If length(n) > 1
, the length is
taken to be the number required.
parameters. Must be strictly positive.
an alternative way to specify the scale.
logical; if TRUE
, probabilities/densities
\(p\) are returned as \(\log(p)\).
logical; if TRUE
(default), probabilities are
\(P[X \le x]\), otherwise, \(P[X > x]\).
order of the moment.
limit of the loss variable.
Vincent Goulet vincent.goulet@act.ulaval.ca and Mathieu Pigeon
The transformed gamma distribution with parameters shape1
\(=
\alpha\), shape2
\(= \tau\) and scale
\(= \theta\) has density:
$$f(x) = \frac{\tau u^\alpha e^{-u}}{x \Gamma(\alpha)}, %
\quad u = (x/\theta)^\tau$$
for \(x > 0\), \(\alpha > 0\), \(\tau > 0\)
and \(\theta > 0\).
(Here \(\Gamma(\alpha)\) is the function implemented
by R's gamma()
and defined in its help.)
The transformed gamma is the distribution of the random variable \(\theta X^{1/\tau},\) where \(X\) has a gamma distribution with shape parameter \(\alpha\) and scale parameter \(1\) or, equivalently, of the random variable \(Y^{1/\tau}\) with \(Y\) a gamma distribution with shape parameter \(\alpha\) and scale parameter \(\theta^\tau\).
The transformed gamma probability distribution defines a family of distributions with the following special cases:
A Gamma distribution when shape2 == 1
;
A Weibull distribution when shape1 ==
1
;
An Exponential distribution when shape2 ==
shape1 == 1
.
The \(k\)th raw moment of the random variable \(X\) is \(E[X^k]\) and the \(k\)th limited moment at some limit \(d\) is \(E[\min(X, d)^k]\), \(k > -\alpha\tau\).
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.
exp(dtrgamma(2, 3, 4, 5, log = TRUE))
p <- (1:10)/10
ptrgamma(qtrgamma(p, 2, 3, 4), 2, 3, 4)
mtrgamma(2, 3, 4, 5) - mtrgamma(1, 3, 4, 5) ^ 2
levtrgamma(10, 3, 4, 5, order = 2)
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