gamlss.inf (version 1.0-2)

term.plotInf0to1: Plot regression terms for a specified parameter of a fitted gamlssInf0to1 object

Description

This is a wrapper to function term.plot. term.plotInf0to1 produces term plots for a specified parameter from a gamlssinf0to1 object.

Usage

term.plotInf0to1(object, parameter = c("mu", "sigma", "nu", "tau", 
        "xi0", "xi1"),...)

Value

A plot of fitted terms.

Arguments

object

a gamlssinf0to1 fitted model

parameter

which distribution (or inflation) parameter is required, default parameter="mu"

...

extra arguments, the same of term.plot (except 'what')

Author

Marco Enea, Mikis Stasinopoulos, Bob Rigby and Abu Hossain

Details

see function term.plot

References

Hossain, A., Stasinopoulos, M., Rigby, R. and Enea, M. (2015). Centile estimation for a proportion response variable. Statistics in Medicine, doi: 10.1002/sim.6748.

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. (2003) Instructions on how to use the GAMLSS package in R. Accompanying documentation in the current GAMLSS help files, (see also https://www.gamlss.com/).

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, https://www.jstatsoft.org/v23/i07.

See Also

gamlssInf0to1

Examples

gen.Family("SST", "logit")
gen.Inf0to1("logitSST","Zero") 
set.seed(10)
Y <- rlogitSSTInf0(500,mu=0.5,sigma=0.7,nu=0.5,tau=5,xi0=0.5,log=FALSE)
dat <- data.frame(Y)
dat$x <- rnorm(500)
m1 <- gamlssInf0to1(y=Y,mu.formula=~x, sigma.formula=~x,
                    nu.formula=~x, tau.formula=~x,
                    xi0.formula=~x,data=dat, family=logitSST)

# term.plot for the mu parameter
term.plot(m1$dist,parameter="mu")
term.plotInf0to1(m1,parameter="mu",col.shaded = 2)

# term.plot for the binomial parameter
term.plot(m1$multinom,parameter="mu")
term.plotInf0to1(m1,parameter="xi0",col.shaded = 2)