Efficiently computing a linear combination of data.table columns

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This is almost 2x faster for me than your manual version:

Reduce("+", lapply(names(DT), function(x) DT[[x]] * cf[x]))

benchmark(manual = DT[, list(cf['A']*A+cf['B']*B+cf['C']*C+cf['D']*D)],
          reduce = Reduce('+', lapply(names(DT), function(x) DT[[x]] * cf[x])))
#    test replications elapsed relative user.self sys.self user.child sys.child
#1 manual          100    1.43    1.744      1.08     0.36         NA        NA
#2 reduce          100    0.82    1.000      0.58     0.24         NA        NA

And to iterate over just mycols, replace names(DT) with mycols in lapply.

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