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I would like to compare every column in my matrix with every other column and get the r-squared. I tried using the following formula and looping through every column: > summary(lm(matrix[,x]~matrix[,y]))$r.squared If I have 10,000 columns, the loops (10,000 * 10,000) take forever even if there is no formula inside. Then, I attempted to vectorize my code: > cor(matrix)^2 With 10,000

I have been using the read.csv function for a while now without any problems. My files are usually 20-50 MBs and they take up to a minute to import. They have all been under 50,000 rows and under 100 columns. Recently, I tried importing a file of a similar size (which means about the same amount of data), but with ~500,000 columns and ~20 rows. The process is taking forever (~1 hour so far). In

I would like to compare every column in my matrix with every other column and get the r-squared. I have been using the following formula and loops: summary(lm(matrix[,x]~matrix[,y]))$r.squared where x and y are the looping column numbers If I have 100 columns (10,000 iterations), the loops give me results in a reasonable time. If I try 10,000 columns, the loops take forever even if there is no