I know I'm off topic and maybe a day late, but I'm pained by the naming of ddof.

It is simply not intuitive for anyone other than the person who thought it up (and from my recollection, maybe not even for him). For one, most stats folk use 'df' as the abbreviation for 'degrees of freedom'. Secondly, the we tend to think of the constant bias adjustment as an ~adjustment~ of the sample size or df. So 'df_adjust=0' or 'sample_adjust=0' will resonate much more.

The other issue is to clearly describe if 'N-1' is obtained by setting the adjustment (whatever it is called) to +1 or -1. There is a reason why most stats packages have different functions or take a parameter to indicate 'sample' versus 'population' variance calculation. Though don't take this as a recommendation to use var and varu -- rather I'm merely pointing out that var(X,

`vardef`

='sample') is an option (using SAS's PROC MEANS parameter name as an arbitrary example).

In the extremely rare cases I need any other denominator, I'm fine with multiplying by var(x)*n/(n-adjust).

-Kevin

On Mon, Apr 7, 2008 at 9:41 AM, Pierre GM <

[hidden email]> wrote:

Anne, Travis,

I have no problem to get rid of varu and stdu in MaskedArray: they were

introduced for my own convenience, and they're indeed outdated with the

introduction of the ddof parameters. I'll get rid of them next time I post

something on the SVN.

_______________________________________________

Numpy-discussion mailing list

[hidden email]

http://projects.scipy.org/mailman/listinfo/numpy-discussion

_______________________________________________

Numpy-discussion mailing list

[hidden email]
http://projects.scipy.org/mailman/listinfo/numpy-discussion