On 01/04/2013 10:13 PM, mary wrote:
Hi,
I'm Marianna
I'm trying to apply the command "repeat" to my matrix but the repeat process
doesn't work as I would.
In particular I would like to apply the function robustm () _that I have
created_ to my two matrices, if the difference between the two matrices is
less than 0.001, R give me back the last matrix.
The code thus created allows me to repeat the process only on the first two
matrices:
function(x) {
for(i in 1:10)
repeat {
b<-robustm(S_X)
b2<-robustm(b)
if(abs(b2[i,i]-b[i,i])<=0.001)
break
}
print(b2)}
in particular S_X is my matrix number1 (already defined, dim 10*10), b2 is
my matrix n.2, if the difference isn't less than my value, I would like
reiterate the process using b2 instead S_X and so on...
(actually serves to me that if the difference is not less than 0.001 the
process starts again taking the last array that has identified as output (in
this case b2) and the remarket in the process creating b3, b4, etc. up to
find the minimum difference between the two matrices and returns me the
last.)
Hi Mary,
In the above, you are testing whether there is at least one absolute
difference less than or equal to 0.001 in the diagonals of two matrices.
One matrix is S_X after applying the "robustm" function and the other is
after a second iteration of "robustm" on the first matrix. So it seems
that "robustm" is a function that hopefully converges on some final value.
First, remember that applying "robustm" to S_X in your repeat loop
doesn't change S_X. Each time you repeat, you will get the same result.
What you may want to do is this:
iterate.robustm<-function(x) {
b<-robustm(x)
finido<-FALSE
while(!finido) {
b2<-robustm(b)
for(i in 1:10)
if(abs(b2[i,i]-b[i,i])<=0.001) finido<-TRUE
b<-b2
}
return(b2)
}
iterate.robustm(S_X)
This iterates "robustm" until at least one diagonal difference is less
than or equal to 0.001. Hopefully that function will always converge.
Jim
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