fastLm() is much slower than lm()

Question

fastLm() is much slower than lm(). Basically, I just call lm() and fastLm() with the same formula and data, but fa

Answer 1

The RcppArmadillo has a better example script in which different version are timed:

edd@max:~/git/rcpparmadillo/inst/examples(master)$ Rscript fastLm.r
                       test replications relative elapsed
4             fLmSEXP(X, y)         5000    1.000   0.174
2         fLmTwoCasts(X, y)         5000    1.017   0.177
3         fLmConstRef(X, y)         5000    1.029   0.179
1          fLmOneCast(X, y)         5000    1.069   0.186
6   fastLmPureDotCall(X, y)         5000    1.218   0.212
5          fastLmPure(X, y)         5000    1.908   0.332
8              lm.fit(X, y)         5000    2.207   0.384
7 fastLm(frm, data = trees)         5000   29.609   5.152
9     lm(frm, data = trees)         5000   36.977   6.434

edd@max:~/git/rcpparmadillo/inst/examples(master)$

The last two use a formula -- and this clearly shows that you do not want to use a formula if you are after speed as deparsing the formula takes a lot longer than actually running the regression. You could set something similar up for RcppEigen, the results will be similar.