gamlss.dist (version 4.3-4)

RGE: Reverse generalized extreme family distribution for fitting a GAMLSS

Description

The function RGE defines the reverse generalized extreme family distribution, a three parameter distribution, for a gamlss.family object to be used in GAMLSS fitting using the function gamlss(). The functions dRGE, pRGE, qRGE and rRGE define the density, distribution function, quantile function and random generation for the specific parameterization of the reverse generalized extreme distribution given in details below.

Usage

RGE(mu.link = "identity", sigma.link = "log", nu.link = "log")
dRGE(x, mu = 1, sigma = 0.1, nu = 1, log = FALSE)
pRGE(q, mu = 1, sigma = 0.1, nu = 1, lower.tail = TRUE, log.p = FALSE)
qRGE(p, mu = 1, sigma = 0.1, nu = 1, lower.tail = TRUE, log.p = FALSE) 
rRGE(n, mu = 1, sigma = 0.1, nu = 1)

Arguments

mu.link

Defines the mu.link, with "identity" link as the default for the mu parameter

sigma.link

Defines the sigma.link, with "log" link as the default for the sigma parameter

nu.link

Defines the nu.link, with "log" link as the default for the nu parameter

x,q

vector of quantiles

mu

vector of location parameter values

sigma

vector of scale parameter values

nu

vector of the shape parameter values

log, log.p

logical; if TRUE, probabilities p are given as log(p).

lower.tail

logical; if TRUE (default), probabilities are P[X <= x],="" otherwise,="" p[x=""> x]

p

vector of probabilities.

n

number of observations. If length(n) > 1, the length is taken to be the number required

Value

• RGE() returns a gamlss.family object which can be used to fit a reverse generalized extreme distribution in the gamlss() function. dRGE() gives the density, pRGE() gives the distribution function, qRGE() gives the quantile function, and rRGE() generates random deviates.

Details

Definition file for reverse generalized extreme family distribution.

The probability density function of the generalized extreme value distribution is obtained from Johnson et al. (1995), Volume 2, p76, equation (22.184) [where $(\xi, \theta, \gamma) \longrightarrow (\mu, \sigma, \nu)$].

The probability density function of the reverse generalized extreme value distribution is then obtained by replacing y by -y and $\mu$ by $-\mu$.

Hence the probability density function of the reverse generalized extreme value distribution with $\nu>0$ is given by

$$f(y|\mu,\sigma, \nu)=\frac{1}{\sigma}\left[1+\frac{\nu(y-\mu)}{\sigma}\right]^{\frac{1}{\nu}-1}S_1(y|\mu,\sigma,\nu)$$

for $$\mu-\frac{\sigma}{\nu}

where

$$S_1(y|\mu,\sigma,\nu)=\exp\left{-\left[1+\frac{\nu(y-\mu)}{\sigma}\right]^\frac{1}{\nu}\right}$$

and where $-\infty<\mu0$ and $\nu>0$. Note that only the case $\nu>0$ is allowed here. The reverse generalized extreme value distribution is denoted as RGE($\mu,\sigma,\nu$) or as Reverse Generalized.Extreme.Family($\mu,\sigma,\nu$).

Note the the above distribution is a reparameterization of the three parameter Weibull distribution given by

$$f(y|\alpha_1,\alpha_2,\alpha_3)=\frac{\alpha_3}{\alpha_2}\left[\frac{y-\alpha_1}{\alpha_2}\right]^{\alpha_3-1} \exp\left[ -\left(\frac{y-\alpha_1}{\alpha_2} \right)^{\alpha_3} \right]$$

given by setting $\alpha_1=\mu-\sigma/\nu$, $\alpha_2=\sigma/\nu$, $\alpha_3=1/\nu$.

References

Rigby, R. A. and Stasinopoulos D. M. (2005). Generalized additive models for location, scale and shape,(with discussion), Appl. Statist., 54, part 3, pp 507-554.

Stasinopoulos D. M., Rigby R.A. and Akantziliotou C. (2006) Instructions on how to use the GAMLSS package in R. Accompanying documentation in the current GAMLSS help files, (see also http://www.gamlss.org/). Stasinopoulos D. M. Rigby R.A. (2007) Generalized additive models for location scale and shape (GAMLSS) in R. Journal of Statistical Software, Vol. 23, Issue 7, Dec 2007, http://www.jstatsoft.org/v23/i07.

See Also

gamlss.family

Examples

RGE()# default links for the reverse generalized extreme family distribution 
newdata<-rRGE(100,mu=0,sigma=1,nu=5) # generates 100 random observations
# library(gamlss)
# gamlss(newdata~1, family=RGE, method=mixed(5,50)) # difficult to converse