R help - Jan 2011 - Problem about for loop

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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Hi,

Looks like the function "theta" takes a variable "data", but
that
variable is not being used in the body of the function (you are using
the global dataX and dataY, which will be the same each time the
function is called).

Martyn

-----Original Message-----
From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-project.org]
On Behalf Of ufuk beyaztas
Sent: 17 January 2011 13:21
To: r-help at r-project.org
Subject: [R] Problem about for loop


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 

-- 
View this message in context:
http://r.789695.n4.nabble.com/Problem-about-for-loop-tp3221210p3221210.h
tml
Sent from the R help mailing list archive at Nabble.com.

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