Hi:
Here's one approach:
X1 <- sample(1:4, 10, replace = TRUE, prob = c(0.4, 0.2, 0.2, 0.2))
foo <- function(x) {
m <- matrix(NA, nrow = length(x), ncol = length(x))
m[, 1] <- x
idx <- seq_len(length(x))
for(j in idx[-1]) {
k <- sample(idx, 2)
x <- replace(x, k, 5)
Dear all
Sorry for simple question:
I want to put the following option into look as number of X is large 1000
variables
X1 <- sample(c(1,2, 3, 4),10, replace = T, prob = c(0.4, 0.2, 0.2, 0.2))
cv1 <- round(runif(2, 1, 10))
# X2 is copy of X1
X2 <- X1
# now X2 is different in cv1 random posi
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