Speed-ups in ProbABEL's logistic regression.
Profiling showed lots of (expensive) calls to exp() and log(). I got rid of ~ 1/3 of the exp() calls by saving the result in a variable and reusing it in the calculation of exp(mu) / ( 1+exp(mu) ).
The number of log() calls was reduced even more by using the fact that sum_i( log(x_i) ) = log( prod_i(x_i) )

In total this gives roughly a speed up of 30% -- 40% when reading txt dosage files and roughly 20% -- 30% when using filevector files (measured for dosage data).


git-svn-id: svn://svn.r-forge.r-project.org/svnroot/genabel@1658 edb9625f-4e0d-4859-8d74-9fd3b1da38cb
Removed some lines from ProbABEL's run_diff.sh, which were inadvertedly introduced by the merge of r1657.





git-svn-id: svn://svn.r-forge.r-project.org/svnroot/genabel@1659 edb9625f-4e0d-4859-8d74-9fd3b1da38cb