Hi, I understand that the glm.fit calls LINPACK fortran routines instead of LAPACK because it can handle the 'rank deficiency problem'. If my data matrix is not rank deficient, would a glm.fit function which runs on LAPACK be faster? Would this be worthwhile to convert glm.fit to use LAPACK? Has anyone done this already?? What is the best way to do this? I'm looking at very large datasets (thousands of glm calls), and would like to know if it's worth the effort for performance issues. Thanks, Ted ------------------------------------- Ted Chiang Bioinformatics Analyst Centre for Computational Biology Hospital for Sick Children, Toronto 416.813.7028 tchiang at sickkids.ca
Hi, I understand that the glm.fit calls LINPACK fortran routines instead of LAPACK because it can handle the 'rank deficiency problem'. If my data matrix is not rank deficient, would a glm.fit function which runs on LAPACK be faster? Would this be worthwhile to convert glm.fit to use LAPACK? Has anyone done this already?? What is the best way to do this? I'm looking at very large datasets (thousands of glm calls), and would like to know if it's worth the effort for performance issues. Thanks, Ted ------------------------------------- Ted Chiang Bioinformatics Analyst Centre for Computational Biology Hospital for Sick Children, Toronto 416.813.7028 tchiang at sickkids.ca