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I have 6 matrices of size 100*50 (e.g. m1-m6) and 6 matrices of size 100*100 (m7-m12). these matrices are nested withing two factors as F and G. I want to create a data structure that reflects this design:

F1 G1 m1 F1 G2 m2 F1 G3 m3 F1 G1 m4 F1 G2 m5 F1 G3 m6 F2 G1 m7 F2 G2 m8 F2 G3 m9 F2 G1 m10 F2 G2 m11 F2 G3 m12

I want to use these structure for ANOVA and plotting the results. Each matrix consists of values over 100 replications. The m1-m12 matrices are stored in csv files.So, I need to import the matrices and create the data structure.I tried array or list but I couldn't find an efficient and correct way for doing that.

Any idea?

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You can use array, First I create data structure:

A1 = array(0,dim=c(100,50,6)) A2 = array(0,dim=c(100,100,6))

I assume you have 2 list of file names , list_files1 and list_files2:

lapply(seq_along(list_files1),function(x){ A1[,,x] <- read.csv(list_files1[[x]]) }) lapply(seq_along(list_files2),function(x){ A2[,,x] <- read.csv(list_files2[[x]]) })
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Thanks for the solution.What do you mean by list file?How can I create it in R?Also, the A1 and A2 has to be combined containing factors.How could it be done?
@Amin I can if you add an example of the expected output. For example edit your question and add an example of the expected output , using 2 matrix of size 2*2 and 2*4.
I want to compare matrices based on the factors.In other words, each matrix has occurred under a specific condition defibed bt factors so factors are indicators of experiment's condition for each matrix.

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