R: Plot regression terms

termplot {base}

R Documentation

Plot regression terms

Description

Plots regression terms against their predictors, optionally with standard errors and partial residuals added.

Usage

termplot(model, data=NULL, envir=environment(formula(model)),
         partial.resid=FALSE, rug=FALSE,
         terms=NULL, se=FALSE, xlabs=NULL, ylabs=NULL, main = NULL,
         col.term = 2, lwd.term = 1.5,
         col.se = "orange", lty.se = 2, lwd.se = 1,
         col.res = "gray", cex = 1, pch = par("pch"),
         ask = interactive() && nb.fig < n.tms && .Device !="postscript",
         use.factor.levels=TRUE,
         ...)

Arguments

model

fitted model object

data

data frame in which variables in model can be found

envir

environment in which variables in model can be found

partial.resid

logical; should partial residuals be plotted?

rug

add rugplots (jittered 1-d histograms) to the axes?

terms

which terms to plot (default NULL means all terms)

se

plot pointwise standard errors?

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.

col.term, lwd.term

color and line width for the “term curve”, see lines.

col.se, lty.se, lwd.se

color, line type and line width for the “twice-standard-error curve” when se = TRUE.

col.res, cex, pch

color, plotting character expansion and type for partial residuals, when partial.resid = TRUE, see points.

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?

...

other graphical parameters

Details

The model object must have a predict method that accepts type=terms, eg glm in the base package, coxph and survreg in the survival package.

For the partial.resid=TRUE option it must have a residuals method that accepts type="partial", which lm and glm do.

The data argument should rarely be needed. One exception is that models with missing data using na.action=na.omit will need to specify a data argument. A work-around is to use na.action=na.exclude instead.

Nothing sensible happens for interaction terms.

Examples

rs <- require(splines)
x <- 1:100
z <- factor(rep(LETTERS[1:4],25))
y <- rnorm(100,sin(x/10)+as.numeric(z))
model <- glm(y ~ ns(x,6) + z)

par(mfrow=c(2,2)) ## 2 x 2 plots for same model :
termplot(model, main = paste("termplot( ", deparse(model$call)," ...)"))
termplot(model, rug=TRUE)
termplot(model, partial=TRUE, rug= TRUE,
         main="termplot(..., partial = TRUE, rug = TRUE)")
termplot(model, partial=TRUE, se = TRUE, main = TRUE)
if(rs) detach("package:splines")