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\name{predict.survreg}\alias{predict.survreg}\alias{predict.survreg.penal}\title{Predicted Values for a `survreg' Object}\description{Predicted values for a \code{survreg} object}\usage{\method{predict}{survreg}(object, newdata,type=c("response", "link", "lp", "linear", "terms", "quantile","uquantile"),se.fit=FALSE, terms=NULL, p=c(0.1, 0.9),...)}\arguments{\item{object}{result of a model fit using the \code{survreg} function.}\item{newdata}{data for prediction. If absent, predictions are for thesubjects used in the original fit.}\item{type}{the type of predicted value.This can be on the original scale of the data (response),the linear predictor (\code{"linear"}, with \code{"lp"} as an allowed abbreviation),a predicted quantile on the original scale of the data (\code{"quantile"}),a quantile on the linear predictor scale (\code{"uquantile"}),or the matrix of terms for the linear predictor (\code{"terms"}).At this time \code{"link"} and linear predictor (\code{"lp"}) are identical.}\item{se.fit}{if TRUE, include the standard errors of the prediction in the result.}\item{terms}{subset of terms. The default for residual type \code{"terms"} is a matrix withone column for every term (excluding the intercept) in the model.}\item{p}{vector of percentiles. This is used only for quantile predictions.}\item{...}{other arguments}}\value{a vector or matrix of predicted values.}\references{Escobar and Meeker (1992). Assessing influence in regression analysis withcensored data. \emph{Biometrics,} 48, 507-528.}\seealso{\code{\link{survreg}}, \code{\link{residuals.survreg}}}\examples{# Draw figure 1 from Escobar and Meekerfit <- survreg(Surv(time,status) ~ age + age^2, data=stanford2,dist='lognormal')plot(stanford2$age, stanford2$time, xlab='Age', ylab='Days',xlim=c(0,65), ylim=c(.01, 10^6), log='y')pred <- predict(fit, newdata=list(age=1:65), type='quantile',p=c(.1, .5, .9))matlines(1:65, pred, lty=c(2,1,2), col=1)}\keyword{survival}