[boost] [Accumulators] is there an updated version?

From: Jamie Allsop (ja11sop_at_[hidden])
Date: 2007-12-29 15:40:34

I recently had a need for some simple statistical analysis of 
performance data and thought rather than sit down and write my own 
functions for mean, variance etc. I'd take the time to learn and use the 
Accumulators library that was accepted into boost on February the 19th 
of this year,
<http://lists.boost.org/boost-announce/2007/02/0114.php>

The only version I could find was that in the vault,
<http://www.boost-consulting.com/vault/index.php?action=downloadfile&filename=accumulators.zip&directory=Math%20-%20Numerics&>

This appears to have been updated last on 21.09.2007 03:32.

The first thing I am wondering is why this library is not in TRUNK now 
that it is a part of boost?

Secondly I thought I'd comment briefly on something that I noticed came 
up during review but has (as yet) not been addressed in the vault 
version. I too assumed that using boost::accumulators::tag::variance 
would return a useful value for variance, unfortunately it returned (in 
my case) what appeared to be an erroneous negative value. The 
'immediate_' form worked ok.

My comment would be that after reading the review there was some debate 
about providing a naive implementation. My thought after spending time 
reading the reviews and browsing the code to try to figure out what was 
happening was that, if I wanted a naive implementation, I could provide 
that easily myself. However I turned to the library to
a) save me writing and maintaining the code, and
b) to enjoy a well thought out implementation by a domain knowledgeable 
implementor.

I therefore think that the natural choices should be accurate 
implementations. If I know enough about my data to realise I can get 
away with a naive implementation that sacrifices accuracy (perhaps for 
performance reasons) then I can select one purposefully.

My first experience with the accumulators library was a mixed bag, but I 
have not used it enough to really form too many opinions on it. I 
suppose when I initially looked at it I thought I would have access to 
statistical algorithms that I could apply to my data, but in fact it 
works differently than that (and I am sure there was a good reason for 
that approach). I'll have to revisit the doc to see if I can find 
understand the motivation better. It works well as it is mind you.

Beyond that the library appears useful and I look forward to making more 
use of it.

I'd be very interested in seeing a newer version of the library that 
addresses the many points highlighted during the review or at least know 
that the library is currently being tidied up and will make into a boost 
release soon :)

Thanks,
Jamie