Nov. 22, 2010
1:56 a.m.
On Sun, Nov 21, 2010 at 19:49, Keith Goodman <kwgoodman@gmail.com> wrote:
But this sample gives a difference:
a = np.random.rand(100) a.var() 0.080232196646619805 var(a) 0.080232196646619791
As you know, I'm trying to make a drop-in replacement for scipy.stats.nanstd. Maybe I'll have to add an asterisk to the drop-in part. Either that, or suck it up and store the damn mean.
The difference is less than eps. Quite possibly, the one-pass version is even closer to the true value than the two-pass version. -- Robert Kern "I have come to believe that the whole world is an enigma, a harmless enigma that is made terrible by our own mad attempt to interpret it as though it had an underlying truth." -- Umberto Eco