prof_term: Plotting the profile deviance of one fitted term
In gamlss.ggplots: Plotting Generalised Additive Model for Location, Scale and Shape

prof_term

R Documentation

Plotting the profile deviance of one fitted term

Description

Plotting the profile deviance of a fitted term in GAMLSS

Usage

prof_term(model = NULL, criterion = c("GD", "GAIC"), 
      penalty = 2.5,  min = NULL, max = NULL, 
      step = NULL, length = 7, xlabel = NULL, plot = TRUE, 
      perc = 95, start.prev = TRUE, line.col = "darkgreen", 
      dash.line.type = 3, dash.line.size = 0.8, text.size = 5, title)

Arguments

`model`	a GAMLSS fitted model
`criterion`	whether Global deviance or GAIC
`penalty`	the penalty k for GAIC
`min`	start from
`max`	finish at
`step`	using step
`length`	if the `step` is left NULL then `length` is considered for evaluating the grid for the parameter. It has a default value of 11.
`xlabel`	if a x label is required
`plot`	whether tto plot the function
`perc`	what percentage confidence interval is required
`start.prev`	whether to start from the previous fitted model parameters values or not (default is TRUE)
`line.col`	the colour of the plotting line
`dash.line.type`	the type of verical dash line for CI's
`dash.line.size`	The size of the dash lines
`text.size`	the size of text
`title`	the title

Details

This function is the ggplot2 version of the original prof.term() function.

Value

creates a plot

Author(s)

Mikis Stasinopoulos

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(aids)
# fitting a linear model
gamlss(y~x+qrt,family=NBI,data=aids)
# testing the linear beta parameter
mod<-quote(gamlss(y ~ offset(this * x) + qrt, data = aids, family = NBI))
prof_term(mod, min=.06, max=0.11)

gamlss.ggplots documentation built on Sept. 3, 2023, 5:08 p.m.