Re: [ferret_users] Sample variance and computing running variance

[Ansley Manke <ansley.b.manke@xxxxxxxx>]

Hi -
1)You make a good point about the variance calculations.  We'll look into this.

2)For a running variance script, I have one simple idea.  This message,
http://www.pmel.noaa.gov/maillists/tmap/ferret_users/fu_2010/msg00685.html

talks about computing a running maximum over a time window (in more recent times we have the SMX and SMN transformations for smoothing using min or max. The above message came before those existed).   It just writes each result to a file and then reads that back in.  It's maybe not elegant, but is straitforward.

-Ansley


On 9/27/2011 9:16 AM, jagadish karmacharya wrote:

Dear ferret users,

I have 2  questions regarding computing variance.

1. sample and population based variance ( equivalently standard deviation):

I have noticed that stat command gives standard deviation based on a sample where as var command gives variance based on a population. My assumption is its customary to calculate sample based variance unless otherwise stated but why does ferret compute variance based on population with var command? I think it is possible to get sample based variance e.g. for my 1-D data with l=140

list/precision=6 v1[l=@var]*v1[l=@ngd]/(v1[l=@ngd]-1)      !  = 7005.65 (this is still slightly different from sample based variance computed from other method e.g. excel gave 7002.42 )

Isn't there a way to compute sample based variance in more straight forward manner and why its not the default option (with var)?

2. Computing running variance:

I am using boxcar smoother transformation (e.g. v1[l=1:140@sbx:31]) to compute running mean but I can't think of a way to compute running variance (standard deviation) in similar manner. My guess is this would involve looping over time but I am not able to work out a way.

Please advice. Thanks in advance.
 
Best regards,

Jagadish