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gamlss.dist (version 4.3-4)

GEOM: Geometric distribution for fitting a GAMLSS model

Description

The function GEOM() defines the Geometric distribution, a one parameter distribution, for a gamlss.family object to be used in GAMLSS fitting using the function gamlss(), with mean equal to the parameter mu. The functions dGEOM, pGEOM, qGEOM and rGEOM define the density, distribution function, quantile function and random generation for the GEOM parameterization of the Geometric distribution.

Usage

GEOM(mu.link = "log")
dGEOM(x, mu = 2, log = FALSE)
pGEOM(q, mu = 2, lower.tail = TRUE, log.p = FALSE)
qGEOM(p, mu = 2, lower.tail = TRUE, log.p = FALSE, max.value=10000)
rGEOM(n, mu = 2)

Arguments

mu.link
Defines the mu.link, with log link as the default for the mu parameter
x, q
vector of quantiles
mu
vector of location 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
max.value
constant; generates a sequence of values for the cdf function.

Value

  • returns a gamlss.family object which can be used to fit a Geometric distribution in the gamlss() function.

Details

The parameterization of the Geometric distribution in the function GEOM is $$f(y|\mu) = (1-p)^y\,p$$ where $p = 1/(mu+1)$ for $y>=0$ and $mu>0$.

References

Johnson, N. L., Kemp, A. W., and Kotz, S. (2005). Univariate discrete distributions. Wiley.

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

Run this code
par(mfrow=c(2,2))
y<-seq(0,20,1)
plot(y, dGEOM(y), type="h")
q <- seq(0, 20, 1)
plot(q, pGEOM(q), type="h")
p<-seq(0.0001,0.999,0.05)
plot(p , qGEOM(p), type="s")
dat <- rGEOM(100)
hist(dat)
#summary(gamlss(dat~1, family=GEOM))

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