The function WEI
can be used to define the Weibull distribution, a two parameter distribution, for a
gamlss.family
object to be used in GAMLSS fitting using the function gamlss()
. [Note that the GAMLSS function WEI2
uses a
different parameterization for fitting the Weibull distribution.]
The functions dWEI
, pWEI
, qWEI
and rWEI
define the density, distribution function, quantile function and random
generation for the specific parameterization of the Weibul distribution.
WEI(mu.link = "log", sigma.link = "log")
dWEI(x, mu = 1, sigma = 1, log = FALSE)
pWEI(q, mu = 1, sigma = 1, lower.tail = TRUE, log.p = FALSE)
qWEI(p, mu = 1, sigma = 1, lower.tail = TRUE, log.p = FALSE)
rWEI(n, mu = 1, sigma = 1)
Defines the mu.link
, with "log" link as the default for the mu parameter, other links are "inverse", "identity" and "own"
Defines the sigma.link
, with "log" link as the default for the sigma parameter, other link is the "inverse", "identity" and "own"
vector of quantiles
vector of the mu parameter
vector of sigma parameter
logical; if TRUE, probabilities p are given as log(p).
logical; if TRUE (default), probabilities are P[X <= x], otherwise, P[X > x]
vector of probabilities.
number of observations. If length(n) > 1
, the length is
taken to be the number required
WEI()
returns a gamlss.family
object which can be used to fit a Weibull distribution in the gamlss()
function.
dWEI()
gives the density, pWEI()
gives the distribution
function, qWEI()
gives the quantile function, and rWEI()
generates random deviates. The latest functions are based on the equivalent R
functions for Weibull distribution.
The parameterization of the function WEI
is given by
$$f(y|\mu,\sigma)=\frac{\sigma y^{\sigma-1}}{\mu^\sigma}
\hspace{1mm} \exp \left[ -\left(\frac{y }{\mu}\right)^{\sigma}
\right] $$
for \(y>0\), \(\mu>0\) and \(\sigma>0\).
The GAMLSS functions dWEI
, pWEI
, qWEI
, and rWEI
can be used to provide the pdf, the cdf, the quantiles and
random generated numbers for the Weibull distribution with argument mu
, and sigma
.
[See the GAMLSS function WEI2
for a different parameterization of the Weibull.]
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.
WEI()
dat<-rWEI(100, mu=10, sigma=2)
# library(gamlss)
# gamlss(dat~1, family=WEI)
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