gamlss: centiles.split – R documentation

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centiles.split

Plots centile curves split by x for a GAMLSS object

Description

This function plots centiles curves for separate ranges of the unique explanatory variable x. It is similar to the centiles function but the range of x is split at a user defined values xcut.point into r separate ranges. The functions also tabulates the sample percentages below each centile curve for each of the r ranges of x (for comparison with the model percentage given by cent) The model should have only one explanatory variable.

Usage

centiles.split(obj, xvar, xcut.points = NULL, n.inter = 4, 
               cent = c(0.4, 2, 10, 25, 50, 75, 90, 98, 99.6), 
               legend = FALSE, main = NULL, main.gsub = "@", 
               ylab = "y", xlab = "x", ylim = NULL, overlap = 0, 
               save = TRUE, plot = TRUE, ...)

Arguments

`obj`	a fitted gamlss object from fitting a gamlss continuous distribution
`xvar`	the unique explanatory variable
`xcut.points`	the x-axis cut off points e.g. `c(20,30)`. If `xcut.points=NULL` then the `n.inter` argument is activated
`n.inter`	if `xcut.points=NULL` this argument gives the number of intervals in which the x-variable will be splited, with default 4
`cent`	a vector with elements the % centile values for which the centile curves are to be evaluated
`legend`	whether a legend is required in the plots or not, the default is `legent=FALSE`
`main`	the main title as character. If NULL the default title (shown the intervals) is shown
`main.gsub`	if the `main.gsub` (with default "@") appears in the `main` title then it is substituted with the default title.
`ylab`	the y-variable label
`xlab`	the x-variable label
`ylim`	the range of the y-variable axis
`overlap`	how much overlapping in the `xvar` intervals. Default value is `overlap=0` for non overlapping intervals
`save`	whether to save the sample percentages or not with default equal to `TRUE`. In this case the functions produce a matrix giving the sample percentages for each interval
`plot`	whether to plot the centles. This option is usefull if the sample statistics only are to be used
`...`	for extra arguments

Value

Centile plots are produced and the sample centiles below each centile curve for each of the r ranges of x can be saved into a matrix.

Warning

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

Author(s)

Mikis Stasinopoulos, d.stasinopoulos@londonmet.ac.uk, Bob Rigby r.rigby@londonmet.ac.uk, with contributions from Elaine Borghie

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/).

Examples

data(abdom)
h<-gamlss(y~pb(x), sigma.formula=~pb(x), family=BCT, data=abdom) 
mout <- centiles.split(h,xvar=abdom$x)
mout
rm(h,mout)

gamlss

Generalised Additive Models for Location Scale and Shape

v5.3-4

GPL-2 | GPL-3

Authors

Mikis Stasinopoulos [aut, cre, cph], Bob Rigby [aut], Vlasios Voudouris [ctb], Calliope Akantziliotou [ctb], Marco Enea [ctb], Daniil Kiose [ctb]

Initial release

2021-03-31