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\name{Predict.matrix}\alias{Predict.matrix}\alias{Predict.matrix2}%- Also NEED an `\alias' for EACH other topic documented here.\title{Prediction methods for smooth terms in a GAM}\description{ Takes \code{smooth} objects produced by \code{smooth.construct} methods and obtains the matrix mappingthe parameters associated with such a smooth to the predicted values of the smooth at a set of new covariate values.In practice this method is often called via the wrapper function \code{\link{PredictMat}}.}\usage{Predict.matrix(object,data)Predict.matrix2(object,data)}%- maybe also `usage' for other objects documented here.\arguments{\item{object}{ is a smooth object produced by a \code{smooth.construct} method function. The objectcontains all the information required to specify the basis for a term of its class, and this information isused by the appropriate \code{Predict.matrix} function to produce a prediction matrix for new covariate values.Further details are given in \code{\link{smooth.construct}}.}\item{data}{A data frame containing the values of the (named) covariates at which the smooth term is to beevaluated. Exact requirements are as for \code{\link{smooth.construct}} and \code{smooth.construct2}}.}\value{ A matrix which will map the parameters associated with the smooth to the vector of values of the smoothevaluated at the covariate values given in \code{object}. If the smooth classis one which generates offsets the corresponding offset is returned asattribute \code{"offset"} of the matrix.}\details{ Smooth terms in a GAM formula are turned into smooth specification objects ofclass \code{xx.smooth.spec} during processing of the formula. Each of these objects isconverted to a smooth object using an appropriate \code{smooth.construct} function. The \code{Predict.matrix}functions are used to obtain the matrix that will map the parameters associated with a smooth term tothe predicted values for the term at new covariate values.Note that new smooth classes can be added by writing a new \code{smooth.construct} method function and acorresponding \code{\link{Predict.matrix}} method function: see the example code provided for\code{\link{smooth.construct}} for details.}\references{Wood S.N. (2017) Generalized Additive Models: An Introduction with R (2nd edition). Chapmanand Hall/CRC Press.}\author{Simon N. Wood \email{simon.wood@r-project.org}}\seealso{ \code{\link{gam}},\code{\link{gamm}},\code{\link{smooth.construct}}, \code{\link{PredictMat}} }\examples{# See smooth.construct examples}\keyword{models} \keyword{smooth} \keyword{regression}%-- one or more ...