Hi everyones, my function like;
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
data.x <- matrix(c(x0,x1,x2,x3,x4),ncol=5)
data.y <- matrix(y,ncol=1)
data.k <- cbind(data.x,data.y)
dataX <- data.k[,1:5]
dataY <- data.k[,6]
theta <- function(data) {
B.cap <- solve(crossprod(dataX)) %*% crossprod(dataX,dataY)
P <- dataX %*% solve(crossprod(dataX)) %*% t(dataX)
Y.cap <- P %*% dataY
e <- dataY - Y.cap
dX <- nrow(dataX) - ncol(dataX)
var.cap <- crossprod(e) / (dX)
ei <- as.vector(dataY - dataX %*% B.cap)
pi <- diag(P)
var.cap.i <- (((dX) * var.cap) / (dX - 1)) -
(ei^2 / ((dX-1) * (1 - pi)))
ti <- ei / sqrt(var.cap * (1 - pi))
Ci <- (ti^2 / (ncol(dataX))) * (pi / (1 - pi))
output.i <- mean(Ci)}
result <- list()
for ( i in 1:5){
data <- replicate(1, data.k[sample(50,50,replace=T),], simplify = FALSE)
output.j <- theta(data)
result <- c(result,(list(output.j))) }
table <- do.call(rbind.data.frame,result)
names(table)=c("cooks")
table
This function give same results each time, the data is changing every time
but mean(Ci)s are always same.
Does anyone have an idea about how to be? Thanks for any idea
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