### Name: predict.survreg
### Title: Predicted Values for a `survreg' Object
### Aliases: predict.survreg predict.survreg.penal
### Keywords: survival

### ** Examples

# Draw figure 1 from Escobar and Meeker
fit <- 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) 

# Predicted Weibull survival curve for a lung cancer subject with
#  ECOG score of 2
lfit <- survreg(Surv(time, status) ~ ph.ecog, data=lung)
pct <- 1:98/100   # The 100th percentile of predicted survival is at +infinity
ptime <- predict(lfit, newdata=data.frame(ph.ecog=2), type='quantile',
                 p=pct, se=TRUE)
matplot(cbind(ptime$fit, ptime$fit + 2*ptime$se.fit,
                         ptime$fit - 2*ptime$se.fit)/30.5, 1-pct,
        xlab="Months", ylab="Survival", type='l', lty=c(1,2,2), col=1)