termplot {base} | R Documentation |
Plots regression terms against their predictors, optionally with standard errors and partial residuals added.
termplot(model, data=model.frame(model), partial.resid=FALSE, rug=FALSE, terms=NULL, se=FALSE, xlabs=NULL, ylab=NULL, main = NULL, col.term = 2, lwd.term = 1.5, col.se = "orange", lty.se = 2, lwd.se = 2, col.res= "gray", cex = 1, pch = par("pch"), ...)
model |
fitted model object |
data |
data frame in which the 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 |
ylab |
label 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 . |
... |
other graphical parameters |
The model object must have a predict
method that accepts
type=terms
, eg glm
in the base package,
coxph
and survreg
in the
survival5
package.
For the partial.resid=TRUE
option it must have a
residuals
method that accepts type="partial"
,
which lm
and glm
do.
It is often necessary to specify the data
argument, because it is
not possible to reconstruct eg x
from a model frame containing
sin(x)
. The data
argument must have exactly the same
rows as the model frame of the model object so, for example, missing
data must have been removed in the same way.
For (generalized) linear models, plot.lm
and
predict.glm
.
rs <- require(splines) x <- 1:100 z <- factor(rep(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 = T, rug = T)") termplot(model, partial=TRUE, se = TRUE, main = TRUE) if(rs) detach("package:splines")