src/library/stats/man/makepredictcall.Rd

% File src/library/stats/man/makepredictcall.Rd
% Part of the R package, https://www.R-project.org
% Copyright 1995-2018 R Core Team
% Distributed under GPL 2 or later

\name{makepredictcall}
\alias{makepredictcall}
\alias{makepredictcall.default}
\alias{SafePrediction}
\title{Utility Function for Safe Prediction}
\description{
  A utility to help \code{\link{model.frame.default}} create the right
  matrices when predicting from models with terms like (univariate)
  \code{poly} or \code{ns}.
}
\usage{
makepredictcall(var, call)
}
\arguments{
  \item{var}{A variable.}
  \item{call}{The term in the formula, as a call.}
}
\details{
  This is a generic function with methods for \code{poly}, \code{bs} and
  \code{ns}: the default method handles \code{scale}.  If
  \code{model.frame.default} encounters such a term when
  creating a model frame, it modifies the \code{predvars} attribute of
  the terms supplied by replacing the term with one which will work for
  predicting new data.  For example \code{makepredictcall.ns} adds
  arguments for the knots and intercept.

  To make use of this, have your model-fitting function return the
  \code{terms} attribute of the model frame, or copy the \code{predvars}
  attribute of the \code{terms} attribute of the model frame to your
  \code{terms} object.

  To extend this, make sure the term creates variables with a class,
  and write a suitable method for that class.
}
\value{
  A replacement for \code{call} for the \code{predvars} attribute of
  the terms.
}
\seealso{
  \code{\link{model.frame}}, \code{\link{poly}}, \code{\link{scale}};
  \code{\link{bs}} and \code{\link{ns}} in package \pkg{splines}.

  \code{\link{cars}} for an example of prediction from a polynomial fit.
}
\examples{
require(graphics)

## using poly: this did not work in R < 1.5.0
fm <- lm(weight ~ poly(height, 2), data = women)
plot(women, xlab = "Height (in)", ylab = "Weight (lb)")
ht <- seq(57, 73, length.out = 200)
nD <- data.frame(height = ht)
pfm <- predict(fm, nD)
lines(ht, pfm)
pf2 <- predict(update(fm, ~ stats::poly(height, 2)), nD)
stopifnot(all.equal(pfm, pf2)) ## was off (rel.diff. 0.0766) in R <= 3.5.0

## see also example(cars)

## see bs and ns for spline examples.
}
\keyword{models}