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.

See Also

For (generalized) linear models, plot.lm and predict.glm.

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")
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