centiles.split: Plots centile curves split by x for a GAMLSS object

Description Usage Arguments Value Warning Author(s) References See Also Examples

View source: R/centilesPlot.R

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

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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/).

See Also

gamlss centiles, centiles.com

Examples

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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)

Example output

Loading required package: splines
Loading required package: gamlss.data
Loading required package: gamlss.dist
Loading required package: MASS
Loading required package: nlme
Loading required package: parallel
 **********   GAMLSS Version 5.0-2  ********** 
For more on GAMLSS look at http://www.gamlss.org/
Type gamlssNews() to see new features/changes/bug fixes.

GAMLSS-RS iteration 1: Global Deviance = 4771.925 
GAMLSS-RS iteration 2: Global Deviance = 4771.039 
GAMLSS-RS iteration 3: Global Deviance = 4770.999 
GAMLSS-RS iteration 4: Global Deviance = 4770.994 
GAMLSS-RS iteration 5: Global Deviance = 4770.993 
     12.22 to 20.07 20.07 to 27.07 27.07 to 34.5 34.5 to 42.5
0.4        0.000000       0.000000     0.6410256    0.6802721
2          2.597403       1.307190     2.5641026    3.4013605
10         8.441558       7.189542    10.8974359    8.1632653
25        24.025974      30.718954    24.3589744   25.8503401
50        46.753247      53.594771    50.0000000   50.3401361
75        73.376623      73.202614    73.7179487   74.8299320
90        88.311688      92.156863    88.4615385   91.1564626
98        97.402597      99.346405    97.4358974   97.9591837
99.6     100.000000      99.346405    99.3589744  100.0000000

gamlss documentation built on March 31, 2021, 5:10 p.m.