# [RC5] Stats suggestion

bwilson at fers.com bwilson at fers.com
Fri Jan 5 07:36:38 EST 2001

```Wow, great idea.  That would solve all of my issues, and would only
require one additional field per participant/team.  Thanks also to Flower
for suggesting the same thing, though yours was a lot easier to
understand.

It sounds like there would be a somewhat complex "catch-up" process to get
all the averages into place.

Do you have a formula handy for calculating k1 and k2 to obtain a given
half-life?

Unfortunately, what I said about SBIII still holds... I don't think we
should attempt this until we have a more robust and reliable platform. But
I can start designing it in my head.

Now I'm really glad I went to the trouble of explaining what I was
thinking.
__
Bruce Wilson, Manager, FERS Business Services
bwilson at fers.com, 312.245.1750, http://www.fers.com/
PGP KeyID: 5430B995, http://www.lasthome.net/~bwilson/
"A good programmer is someone who looks
both ways before crossing a one-way street."

Ben Clifford <benc at hawaga.org.uk>
Sent by: owner-rc5 at lists.distributed.net
2001-01-05 06:04

To:     rc5 at lists.distributed.net
cc:
Subject:        Re: [RC5] Stats suggestion

Have you considered an "exponential decay" average?

This is a weighted average, where the more recent values have a bigger
weight than values in the past - values in the distant past have such a
tiny weight that they are insignificant.

Its advantage from a distributed.net point of view is that it only needs
one piece of historical data, yesterdays exponential average.

It can be computed as:

todays_avg = k1 * yesterdays_avg + k2 * todays_count;

with suitably chosen (related) k1 and k2 constants.

Varying the constants changes the "decay rate" of the average - I would
think for distributed.net, half lives of 7-days, 30-days and 60-days would
probably be appropriate.

For people who use unix, this is how load averages from the uptime command
are computed.

This metric needs very little storage and is quick to compute. It

It is not as "jumpy" as a n-day average - if I have a spike, then my
30-day average will jump up and in 30 days will suddenly drop

I'm not sure how well I have explained this... please ask questions :-)

Ben

--
http://www.custom-networks.co.uk/

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