> Yes, sounds like a good idea to me. Go ahead and add it in > covariance_source.c if you have the 1-pass algorithm.
Ok, added under gsl_stats_correlation. I tested it successfully with the data set: x = 9.0e9 + i + 1 y = 9.0e9 - i - 1 for i = 1..100 which normally causes bad codes to fail. Also tested it with lots of random x/y vectors and compared against the result of: gsl_stats_covariance(x,y) / (gsl_stats_sd(x) * gsl_stats_sd(y)) all with excellent results - error was below GSL_DBL_EPSILON in all cases - the test codes in statistics/ aren't really set up for this type of exhaustive testing...so I just adapted the test that is in there for the correlation routine. Patrick Alken
