Hi dear all,
The code like this;
e <- rnorm(n=50, mean=0, sd=sqrt(0.5625))
x0 <- c(rep(1,50))
x1 <- rnorm(n=50,mean=2,sd=1)
x2 <- rnorm(n=50,mean=2,sd=1)
x3 <- rnorm(n=50,mean=2,sd=1)
x4 <- rnorm(n=50,mean=2,sd=1)
y <- 1+ 2*x1+4*x2+3*x3+2*x4+e
x2[1] = 10 #influential observarion
y[1] = 10 #influential observarion
X <- matrix(c(x0,x1,x2,x3,x4),ncol=5)
Y <- matrix(y,ncol=1)
Design.data <- cbind(X, Y)
result <- list ()
for( i in 1: 3100) {
data <- Design.data[sample(50,50,replace=TRUE),]
dataX <- data[,1:5]
dataY <- data[,6]
B.cap.simulation <- solve(crossprod(dataX)) %*% crossprod(dataX, dataY)
P.simulation <- dataX %*% solve(crossprod(dataX)) %*% t(dataX)
Y.cap.simulation <- P.simulation %*% dataY
e.simulation <- dataY - Y.cap.simulation
dX.simulation <- nrow(dataX) - ncol(dataX)
var.cap.simulation <- crossprod(e.simulation) / (dX.simulation)
ei.simulation <- as.vector(dataY - dataX %*% B.cap.simulation)
pi.simulation <- diag(P.simulation)
var.cap.i.simulation <- (((dX.simulation) *
var.cap.simulation)/(dX.simulation - 1)) -
(ei.simulation^2/((dX.simulation - 1) * (1 - pi.simulation)))
ti.simulation <- ei.simulation / sqrt(var.cap.simulation * (1 -
pi.simulation))
ti.star.simulation <- ei.simulation / sqrt(var.cap.i.simulation * (1 -
pi.simulation))
pi.star.simulation <- pi.simulation + ei.simulation^2 /
crossprod(e.simulation)
WKi.simulation <- (ti.star.simulation)*sqrt(pi.simulation/(1-pi.simulation))
result<- c(result,list(WKi.simulation))
}
Finally i get the result which contains 3100 WKi.simulation. I'm trying to
get a subset for those subset do not contain any Y[1,] that is point 10. Can
anyone help me about how to be?
Thanks for any idea...
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