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

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.

1 2 3 4 5 |

`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. |

`n.inter` |
if |

`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 |

`main` |
the main title as character. If NULL the default title (shown the intervals) is shown |

`main.gsub` |
if the |

`ylab` |
the y-variable label |

`xlab` |
the x-variable label |

`ylim` |
the range of the y-variable axis |

`overlap` |
how much overlapping in the |

`save` |
whether to save the sample percentages or not with default equal to |

`plot` |
whether to plot the centles. This option is usefull if the sample statistics only are to be used |

`...` |
for extra arguments |

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.

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

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

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/).

1 2 3 4 5 |

```
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
```

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