Hi all, Recently I sent an email and I was asked to provide reproducible code of a simple example of my situation. Instead of providing the code, I decided to describe what I need in my code. I've written a function V, which is a function of (r,s); so I have a function V(r,s) in fact. The output of V is a (n-1) dimensional vector, where n is the sample size. What I need is to calculate the following steps *for all possible values of (r,s)*: 1- Calculate V(r,s) for m replicates. 2- Calculate the mean of these m replicates. 3- Calculate the difference of each of m V(r,s) and the mean in step 3. 4- Calculate the absolute values of the differences in step 3. 5- Calculate the mean of the m differences calculated in step 4. So at the end I'll have r0*s0 vectors (with dimension n-1), where r0 and s0 are the number of possible values of r and s respectively. My main problem is that I don't know how I should keep the replicates of V's (produced in step 2) for calculating the differences in step 3 , regarding that I should consider all possible values of r and s. Some people suggested using arrays, but some other said it could work very slowly. I've never used arrays, so I don't know if it's a good idea or there are better ideas as well. Thanks for any help in advance
question
2 messages · Mahdiyeh Erfaniyan, Boris Steipe
That all sounds so straightforward I wonder why you don't just code it up and try it out. You might profit from the advice of chapter 2 of the R-Inferno for your "main problem". If "some people" who you ask for advice think that arrays in R are intrinsically slow, you might also want to look for other people. Cheers, B. (Did I mention: don't post in HTML? No. Ok. Don't post in HTML.)
On Apr 13, 2015, at 2:51 PM, Mahdiyeh Erfaniyan <mahdiyeh.erfaniyan at gmail.com> wrote:
Hi all, Recently I sent an email and I was asked to provide reproducible code of a simple example of my situation. Instead of providing the code, I decided to describe what I need in my code. I've written a function V, which is a function of (r,s); so I have a function V(r,s) in fact. The output of V is a (n-1) dimensional vector, where n is the sample size. What I need is to calculate the following steps *for all possible values of (r,s)*: 1- Calculate V(r,s) for m replicates. 2- Calculate the mean of these m replicates. 3- Calculate the difference of each of m V(r,s) and the mean in step 3. 4- Calculate the absolute values of the differences in step 3. 5- Calculate the mean of the m differences calculated in step 4. So at the end I'll have r0*s0 vectors (with dimension n-1), where r0 and s0 are the number of possible values of r and s respectively. My main problem is that I don't know how I should keep the replicates of V's (produced in step 2) for calculating the differences in step 3 , regarding that I should consider all possible values of r and s. Some people suggested using arrays, but some other said it could work very slowly. I've never used arrays, so I don't know if it's a good idea or there are better ideas as well. Thanks for any help in advance [[alternative HTML version deleted]]
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