R: Comparing centiles from different GAMLSS models

centiles.com {gamlss} | R Documentation

## Comparing centiles from different GAMLSS models

### Description

This function compares centiles curves for more than one GAMLSS objects.It is based on the `centiles` function. 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.com(obj, ..., xvar, cent = c(0.4, 10, 50, 90, 99.6),
                 legend = TRUE, ylab = "y", xlab = "x", xleg = min(xvar),
                 yleg = max(obj$y), xlim = range(xvar), ylim = NULL,
                 no.data = FALSE, color = TRUE, main = NULL, plot = TRUE)

### Arguments

`obj` | a fitted gamlss object from fitting a gamlss continuous distribution
`...` | optionally more fitted GAMLSS model objects
`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
`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
`no.data` | whether the data should plotted, default `no.data=FALSE` or not `no.data=TRUE`
`color` | whether the fitted centiles are shown in colour, `color=TRUE` (the default) or not `color=FALSE`
`main` | the main title
`plot` | whether to plot the centiles

### Value

Centile plots are produced for the different fitted models and the sample centiles below each centile curve are printed

### Warning

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

### Author(s)

Mikis Stasinopoulos d.stasinopoulos@londonmet.ac.uk and Bob Rigby r.rigby@londonmet.ac.uk

### 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.

Rigby, R. A., Stasinopoulos, D. M., Heller, G. Z., and De Bastiani, F. (2019) Distributions for modeling location, scale, and shape: Using GAMLSS in R, Chapman and Hall/CRC. An older version can be found in 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/.

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.

(see also https://www.gamlss.com/).

### See Also

`gamlss`, `centiles` , `centiles.split`

### Examples

    data(abdom)
    h1<-gamlss(y~cs(x,df=3), sigma.formula=~cs(x,1),family=BCT, data=abdom)
    h2<-gamlss(y~pb(x), sigma.formula=~pb(x), family=BCT, data=abdom )
    centiles.com(h1,h2,xvar=abdom$x)
    rm(h1,h2)

[Package gamlss version 5.3-2 Index]