| termplot {stats} | R Documentation |
Plots regression terms against their predictors, optionally with standard errors and partial residuals added.
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"),
col.smth = "darkred", lty.smth = 2, span.smth = 2/3,
ask = interactive() && nb.fig < n.tms &&
.Device != "postscript",
use.factor.levels = TRUE, smooth = NULL, ...)
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? |
smooth |
NULL or a function with the same arguments as
panel.smooth to draw a smooth through the partial
residuals for non-factor terms |
lty.smth,col.smth, span.smth |
Passed to smooth |
... |
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 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, 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.
For (generalized) linear models, plot.lm and
predict.glm.
had.splines <- "package:splines" %in% search()
if(!had.splines) 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, se = TRUE, main = TRUE)
termplot(model, partial=TRUE, smooth=panel.smooth,span.smth=1/4)
if(!had.splines && rs) detach("package:splines")