n <nrow(law) theta.b <-numeric(B) for (b in 1:B){ i <-sample(1:n,size n,replace TRUE) LSAT <law$LSAT[i] GPA <law$GPA[i] theta.b[b]<-cor(LSAT,GPA) ] bias <-mean(theta.b-theta.hat) bias Code 这个值和例3中的boot函数返回的结果非常相近 例5 Bootstrap偏差估计：假设x=(e1,·,c10)~N(4,g2),求a的估计 量2=∑1（红：-）的偏差 TCode n<-10 x<-rnorm(n,mean=0,sd=10) Previous Next First Last Back Forward 13n <- nrow(law) theta.b <- numeric(B) for (b in 1:B) { i <- sample(1:n, size = n, replace = TRUE) LSAT <- law$LSAT[i] GPA <- law$GPA[i] theta.b[b] <- cor(LSAT, GPA) } bias <- mean(theta.b - theta.hat) bias ↓Code ˘áä⁄~3•bootºÍà£(Jö~ÉC. ~5 Bootstrap†O: bx = (x1, · · · , x10) ∼ N(µ, σ2 ), ¶σ 2O ˛ σˆ 2 = 1 n Pn i=1(xi − x¯) 2† ↑Code n<-10 x<-rnorm(n,mean=0,sd=10) Previous Next First Last Back Forward 13