trimmed.mse <-function(n,m,k,p){ #MC est of mse for k-level trimmed mean of #contaminated normal pN(0,1)+(1-p)N(0,100) tmean <numeric(m) for (i in 1:m){ sigma <sample(c(1,10),size n, replace TRUE,prob =c(p,1-p)) x <-sort(rnorm(n,0,sigma)) tmean[i]<-sum(x[(k+1):(n-k)])/(n-2*k) mse.est <-mean(tmean2) se.mse <-sqrt(mean((tmean-mean(tmean))2))/sqrt(m) return(c(mse.est,se.mse)) ] for (k in 0:K){ mse[k+1,1:2]<-trimmed.mse(n=n,m=m,k=k,p=1.0) mse[k+1,3:4]<-trimmed.mse(n=n,m=m,k=k,p=.95) mse[k+1,5:6]<-trimmed.mse(n=n,m=m,k=k,p=.9) round(n*mse,3) ↓Ccdn Previous Next First Last Back Forward 9trimmed.mse <- function(n, m, k, p) { #MC est of mse for k-level trimmed mean of #contaminated normal pN(0,1) + (1-p)N(0,100) tmean <- numeric(m) for (i in 1:m) { sigma <- sample(c(1, 10), size = n, replace = TRUE, prob = c(p, 1-p)) x <- sort(rnorm(n, 0, sigma)) tmean[i] <- sum(x[(k+1):(n-k)]) / (n-2*k) } mse.est <- mean(tmean^2) se.mse <- sqrt(mean((tmean-mean(tmean))^2)) / sqrt(m) return(c(mse.est, se.mse)) } for (k in 0:K) { mse[k+1, 1:2] <- trimmed.mse(n=n, m=m, k=k, p=1.0) mse[k+1, 3:4] <- trimmed.mse(n=n, m=m, k=k, p=.95) mse[k+1, 5:6] <- trimmed.mse(n=n, m=m, k=k, p=.9) } round(n*mse,3) ↓Code Previous Next First Last Back Forward 9