term.plot: Plot regression terms for a specified parameter of a fitted...

In gamlss: Generalized Additive Models for Location Scale and Shape

Plot regression terms for a specified parameter of a fitted GAMLSS object

Description

Plots regression terms against their predictors, optionally with standard errors and partial residuals added. It is based on the R function termplot but is suitably changed to apply to GAMLSS objects.

Usage

term.plot(object, what = c("mu", "sigma", "nu", "tau"), 
         parameter= NULL, data = NULL, 
         envir = environment(formula(object)), partial.resid = FALSE, 
         rug = FALSE, terms = NULL, se = TRUE, ylim = c("common", "free"), 
         scheme = c("shaded", "lines"), xlabs = NULL, ylabs = NULL, 
         main = NULL, pages = 0, col.term = "darkred", 
         col.se = "orange", col.shaded = "gray", col.res = "lightblue", 
         col.rug = "gray", lwd.term = 1.5, lty.se = 2, lwd.se = 1, 
         cex.res = 1, pch.res = par("pch"), 
         ask = interactive() && nb.fig < n.tms && .Device != "postscript", 
         use.factor.levels = TRUE, surface.gam = FALSE,     
         polys = NULL, polys.scheme = "topo",...)

Arguments

object	a fitted GAMLSS object
what	the required parameter of the GAMLSS distribution i.e. "mu"
parameter	equivalent to what
data	data frame in which variables in object can be found
envir	environment in which variables in object can be found
partial.resid	logical; should partial residuals be plotted or not
rug	add rug plots (jitter 1-d histograms) to the axes?
terms	which terms to be plotted (default 'NULL' means all terms)
se	plot point-wise standard errors?
ylim	there are two options here a) "common" and b) "free". The "common" option plots all figures with the same ylim range and therefore allows the viewer to check the relative contribution of each terms compare to the rest. In the‘free’ option the limits are computed for each plot separately.
scheme	whether the se's should appear shaded or as lines
xlabs	vector of labels for the x axes
ylabs	vector of labels for the y axes
main	logical, or vector of main titles; if 'TRUE', the model's call is taken as main title, 'NULL' or 'FALSE' mean no titles.
pages	in how many pages the plot should appear. The default is 0 which allows different page for each plot
col.term	the colour of the term line
col.se	the colour of the se's lines
col.shaded	the colour of the shaded area
col.res	the colour of the partial residuals
col.rug	the colour of the rug
lwd.term	line width of the fitted terms
lty.se	line ype for standard errors
lwd.se	line width for the stadard errors
cex.res	plotting character expansion for the partial residuals
pch.res	characters for points in the partial residuals
ask	logical; if 'TRUE', the user is asked before each plot, see 'par(ask=.)'.
use.factor.levels	Should x-axis ticks use factor levels or numbers for factor terms?
surface.gam	whether to use surface plot if a ga() term is fitted
polys	The polygon information file for MRF models
polys.scheme	Color scheme for polygons for RMF models
...	other graphical parameters

Details

The function uses the lpred function of GAMLSS. The 'data' argument should rarely be needed, but in some cases 'termplot' may be unable to reconstruct the original data frame. Using 'na.action=na.exclude' makes these problems less likely. Nothing sensible happens for interaction terms.

Value

a plot of fitted terms.

Author(s)

Mikis Stasinopoulos based on the existing termplot() function

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

termplot

Examples

data(aids)
a<-gamlss(y~pb(x)+qrt,data=aids,family=NBI)
term.plot(a, pages=1)
rm(a)

gamlss documentation built on May 29, 2024, 6:08 a.m.