# leave-one-out and 6-fold cross-validation prediction error for # the mammals data set.data(mammals, package="MASS")mammals.glm <- glm(log(brain) ~ log(body), data = mammals)(cv.err <- cv.glm(mammals, mammals.glm)$delta)(cv.err.6 <- cv.glm(mammals, mammals.glm, K = 6)$delta)# As this is a linear model we could calculate the leave-one-out # cross-validation estimate without any extra model-fitting.muhat <- fitted(mammals.glm)mammals.diag <- glm.diag(mammals.glm)(cv.err <- mean((mammals.glm$y - muhat)^2/(1 - mammals.diag$h)^2))
最近写文章时需要用到这个方法，但看的是云里雾里，请高手指教，这里(cv.err <- cv.glm(mammals, mammals.glm)$delta)，还有最后一行是什么意思，谢谢