Hello,
Make a _simple_ example, I don't see what packages like knitr or ggplot2
have anything to do with your problem.
Like this is, I think you're asking too much from r-help.
Rui Barradas
Em 19-10-2013 23:38, Laz escreveu:
Dear R users,
Dear R users,
(I had not included two more function
Dear R users,
Dear R users,
(I had not included two more functions in the previous mail. This
version is complete)
There is a small problem which I don't know how to sort it out, based on
the former example I had explained earlier own.
I am calling my own functions which are based on simulat
Dear R users,
There is a small problem which I don't know how to sort it out, based on
the former example I had explained earlier own.
I am calling my own three functions which are based on simulations as below:
library(gmp)
library(knitr) # load this packages for publishing results
library(mat
Thank you so very much!
It works like a charm !!!
Regards,
Laz
On 10/19/2013 5:03 PM, Rui Barradas wrote:
fun <- function(n = 10){
matd <- matrix(sample(1:30,30, replace=FALSE), ncol=5, nrow=6)
res <- list(mat = NULL, Design_best = matd, Original_design = matd)
trace <- sum(diag(mat
Hello,
Seems simple.
fun <- function(n = 10){
matd <- matrix(sample(1:30,30, replace=FALSE), ncol=5, nrow=6)
res <- list(mat = NULL, Design_best = matd, Original_design = matd)
trace <- sum(diag(matd))
res$mat <- rbind(res$mat, c(trace = trace, iterations = 0))
Dear R users,
Suppose I want to randomly generate some data, in matrix form, randomly
swap some of the elements and calculate trace of the matrix for each of
these stages. If the value of trace obtained in the later is bigger than
the former, drop the latter matrix and go back to the former ma
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