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% File src/library/stats/man/termplot.Rd
% Part of the R package, https://www.R-project.org
% Copyright 1995-2021 R Core Team
% Distributed under GPL 2 or later
\name{termplot}
\alias{termplot}
\title{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"),
col.smth = "darkred", lty.smth = 2, span.smth = 2/3,
ask = dev.interactive() && nb.fig < n.tms,
use.factor.levels = TRUE, smooth = NULL, ylim = "common",
plot = TRUE, transform.x = FALSE, \dots)
}
\arguments{
\item{model}{fitted model object}
\item{data}{data frame in which variables in \code{model} can be
found}
\item{envir}{environment in which variables in \code{model} can be found}
\item{partial.resid}{logical; should partial residuals be plotted?}
\item{rug}{add \link{rug}plots (jittered 1-d histograms) to the axes?}
\item{terms}{which terms to plot (default \code{NULL} means all
terms); a vector passed to
\code{\link{predict}(.., type = "terms", terms = *)}.}
\item{se}{plot pointwise standard errors?}
\item{xlabs}{vector of labels for the x axes}
\item{ylabs}{vector of labels for the y axes}
\item{main}{logical, or vector of main titles; if \code{TRUE}, the
model's call is taken as main title, \code{NULL} or \code{FALSE} mean
no titles.}
\item{col.term, lwd.term}{color and line width for the \sQuote{term curve},
see \code{\link{lines}}.}
\item{col.se, lty.se, lwd.se}{color, line type and line width for the
\sQuote{twice-standard-error curve} when \code{se = TRUE}.}
\item{col.res, cex, pch}{color, plotting character expansion and type
for partial residuals, when \code{partial.resid = TRUE}, see
\code{\link{points}}.}
\item{ask}{logical; if \code{TRUE}, the user is \emph{ask}ed before
each plot, see \code{\link{par}(ask=.)}.}
\item{use.factor.levels}{Should x-axis ticks use factor levels or
numbers for factor terms?}
\item{smooth}{\code{NULL} or a function with the same arguments as
\code{\link{panel.smooth}} to draw a smooth through the partial
residuals for non-factor terms}
\item{lty.smth, col.smth, span.smth}{Passed to \code{smooth}}
\item{ylim}{an optional range for the y axis, or \code{"common"} when
a range sufficient for all the plot will be computed, or
\code{"free"} when limits are computed for each plot.}
\item{plot}{if set to \code{FALSE} plots are not produced: instead a
list is returned containing the data that would have been plotted.}
\item{transform.x}{logical vector; if an element (recycled as necessary)
is \code{TRUE}, partial residuals for the corresponding term are
plotted against transformed values.
The model response is then a straight line, allowing a
ready comparison against the data or against the curve
obtained from \code{smooth-panel.smooth}.}
\item{\dots}{other graphical parameters.}
}
\details{
The \code{model} object must have a \code{predict} method that accepts
\code{type = "terms"}, e.g., \code{\link{glm}} in the \pkg{stats} package,
\code{\link[survival]{coxph}} and \code{\link[survival]{survreg}} in
the \CRANpkg{survival} package.
For the \code{partial.resid = TRUE} option \code{model} must have a
\code{\link{residuals}} method that accepts \code{type = "partial"},
which \code{\link{lm}} and \code{\link{glm}} do.
The \code{data} argument should rarely be needed, but in some cases
\code{termplot} may be unable to reconstruct the original data
frame. Using \code{na.action=na.exclude} makes these problems less likely.
Nothing sensible happens for interaction terms, and they may cause errors.
The \code{plot = FALSE} option is useful when some special action is needed,
e.g.\sspace{}to overlay the results of two different models or to plot
confidence bands.
}
\value{
For \code{plot = FALSE}, a list with one element for each plot which
would have been produced. Each element of the list is a data frame
with variables \code{x}, \code{y}, and optionally the pointwise
standard errors \code{se}. For continuous predictors \code{x} will
contain the ordered unique values and for a factor it will be a factor
containing one instance of each level. The list has attribute
\code{"constant"} copied from the predicted terms object.
Otherwise, the number of terms, invisibly.
}
\seealso{For (generalized) linear models, \code{\link{plot.lm}} and
\code{\link{predict.glm}}.}
\examples{
require(graphics)
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.resid = TRUE, se = TRUE, main = TRUE)
termplot(model, partial.resid = TRUE, smooth = panel.smooth, span.smth = 1/4)
if(!had.splines && rs) detach("package:splines")
if(requireNamespace("MASS", quietly = TRUE)) {
hills.lm <- lm(log(time) ~ log(climb)+log(dist), data = MASS::hills)
termplot(hills.lm, partial.resid = TRUE, smooth = panel.smooth,
terms = "log(dist)", main = "Original")
termplot(hills.lm, transform.x = TRUE,
partial.resid = TRUE, smooth = panel.smooth,
terms = "log(dist)", main = "Transformed")
}}
\keyword{hplot}
\keyword{regression}