gamlss.inf (version 1.0-2)

centiles.Inf0to1: Plotting centile curves for a gamlssInf0to1 and gamlssZadj object

Description

Function centiles.Inf0to1() plots centile curves for distributions belonging to the GAMLSS family of distributions defined in the intervals (0,1],[0,1) and [0,1]. The function also tabulates the sample percentages below each centile curve (for comparison with the model percentages given by the argument cent). A restriction of the function is that it applies to models with one explanatory variable only.

Usage

centiles.Inf0to1(obj, xvar = NULL, cent = c(0.4, 2, 10, 25, 50, 75, 
    90, 98, 99.6), legend = TRUE, ylab = "y", xlab = "x", main = NULL, 
    main.gsub = "@", xleg = min(xvar), yleg = max(obj$y), xlim = range(xvar), 
    ylim = range(obj$y), save = FALSE, plot = TRUE, points = TRUE, 
    pch = 15, cex = 0.5, col = gray(0.7), col.centiles = 1:length(cent) + 
        2, lty.centiles = 1, lwd.centiles = 1, ...)
centiles.Zadj(obj, xvar = NULL, cent = c(0.4, 2, 10, 25, 50, 75, 
   90, 98, 99.6), legend = TRUE, ylab = "y", xlab = "x", main = NULL, 
   main.gsub = "@", xleg = min(xvar), yleg = max(obj$y), xlim = range(xvar), 
   ylim = range(obj$y), save = FALSE, plot = TRUE, points = TRUE, 
   pch = 15, cex = 0.5, col = gray(0.7), col.centiles = 1:length(cent) + 
   2, lty.centiles = 1, lwd.centiles = 1, ...)

Value

A centile plot is produced and the sample centiles below each centile curve are printed (or saved)

Arguments

obj

a fitted gamlss object from fitting a gamlss distribution

xvar

the unique explanatory variable

cent

a vector with elements the % centile values for which the centile curves have to be evaluated

legend

whether a legend is required in the plot or not, the default is legent=TRUE

ylab

the y-variable label

xlab

the x-variable label

main

the main title here as character. If NULL the default title "centile curves using NO" (or the relevant distributions name) is shown

main.gsub

if the main.gsub (with default "@") appears in the main title then it is substituted with the default title.

xleg

position of the legend in the x-axis

yleg

position of the legend in the y-axis

xlim

the limits of the x-axis

ylim

the limits of the y-axis

save

whether to save the sample percentages or not with default equal to FALSE. In this case the sample percentages are printed but are not saved

plot

whether to plot the centiles

points

whether the data points should be plotted, default is TRUE

pch

the character to be used as the default in plotting points see par

cex

size of character see par

col

plotting colour see par

col.centiles

Plotting colours for the centile curves

lty.centiles

line type for the centile curves

lwd.centiles

The line width for the centile curves

...

for extra arguments

Author

Mikis Stasinopoulos , Bob Rigby with contribution from Steve Ellison

Warning

This function is appropriate only when one continuous explanatory variable is fitted in the model

Details

Centiles are calculated using the fitted values in obj and xvar must correspond exactly to the predictor in obj to plot correctly.

col.centiles, lty.centiles and lwd.centiles may be vector arguments and are recycled to the length cent if necessary.

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 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.

Houssain, A., Stasinopoulos, M., Rigby, R. and Enea, M. (2015). Centile estimation for a proportion response variable. Accepted for publication on Statistics in Medicine.

See Also

gamlssInf0to1, gamlss, centiles.split , centiles.com

Examples

if (FALSE) {
gen.Family("SST", "logit")
gen.Inf0to1("logitSST","One") 
set.seed(30)
x <- seq(0,1,l=2000)
dat <- data.frame(x)
dat$Y <- rlogitSSTInf1(2000,mu=-3+10*x-0.7*x^2,sigma=0.9,nu=0.5,
                       tau=5,xi1=plogis(-0.5*ifelse(x>0.7,-1,13)),log=FALSE)

m1 <- gamlssInf0to1(y=Y,mu.formula=~pb(x), sigma.formula=~pb(x),
                    nu.formula=~pb(x), tau.formula=~pb(x),
                    xi1.formula=~pb(x),
                    data=dat, family=logitSST)

centiles.Inf0to1(m1,xvar= dat$x, cent=c(2,10,25,50,75,90,98),
col.centiles=c(1,7:2),
ylab="proportion", xlab="x",legend=FALSE,main="(c) Inf. logitSST")
}