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...=shape) model<-survreg(Surv(y)~1,dist="weibull") ### Exp of coef and predict are the same exp(model$coef) predict(model,type=c("response"))[1] ### Here is the mean and median of the data mean(y) median(y) ### Fitted Mean and Median from survreg fitScale<-exp(model$coef) fitShape<-1/model$scale fitScale*gamma(1 + 1/fitShape) fitScale*(log(2))^(1/fitShape) Is this done on purpose? If so does anyone know why? Thanks in advance, Sean Brummel [[alternative HTML version deleted]]

...ewx) wrongmeanshift <- wrongmean + 0.2 wrongper <- pgamma(wrongmeanshift, wrongshape, wrongrate) nfalseundermean <- which(abs(newx-wrongmeanshift)==min(abs(newx-wrongmeanshift))) initnfalse <- nfalseundermean / wrongper fitmean <- -1 fitsd <- 0 fitnfalse <- initnfalse fitshape <- wrongshape fitrate <- wrongrate curve((fitnfalse*dgamma(x,fitshape,fitrate))/totalx, add=T, col="red", lwd=2) breaksllength <- length(goodhist$breaks) endi = breaksllength - 1 binprob = c(1) for (i in 1:endi) { expnegative <- fitnfalse * (pgamma(goodhist$breaks[i+1...