Description Usage Arguments Details Value Warning Note Author(s) References See Also Examples
The function WEI3
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()
.
This is a parameterization of the Weibull distribution where mu is the mean of the distribution.
[Note that the GAMLSS functions WEI
and WEI2
use
different parameterizations for fitting the Weibull distribution.]
The functions dWEI3
, pWEI3
, qWEI3
and rWEI3
define the density, distribution function, quantile function and random
generation for the specific parameterization of the Weibull distribution.
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mu.link |
Defines the |
sigma.link |
Defines the |
x,q |
vector of quantiles |
mu |
vector of the mu parameter values |
sigma |
vector of sigma 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 |
The parameterization of the function WEI3
is given by
f(y|mu,sigma)= (sigma/beta)*(y/beta)^(sigma-1)exp(-(y/beta)^sigma)
where mu/(Gamma((1/sigma)+1)) for y>0, μ>0 and σ>0.
The GAMLSS functions dWEI3
, pWEI3
, qWEI3
, and rWEI3
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 WEI
for a different parameterization of the Weibull.]
WEI3()
returns a gamlss.family
object which can be used to fit a Weibull distribution in the gamlss()
function.
dWEI3()
gives the density, pWEI3()
gives the distribution
function, qWEI3()
gives the quantile function, and rWEI3()
generates random deviates. The latest functions are based on the equivalent R
functions for Weibull distribution.
In WEI3
the estimated parameters mu
and sigma
can be highly correlated so it is advisable to use the
CG()
method for fitting [as the RS() method can be very slow in this situation.]
The mean in WEI3
is given by mu and the variance
mu^2(Gamma(1/sigma +1)/Gamma(1/sigma+1)^2 -1)
Bob Rigby and Mikis Stasinopoulos mikis.stasinopoulos@gamlss.org
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.
Stasinopoulos D. M., Rigby R.A., Heller G., Voudouris V., and De Bastiani F., (2017) Flexible Regression and Smoothing: Using GAMLSS in R, Chapman and Hall/CRC.
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