Hi.
On Mon, 21 Mar 2016 23:06:39 -0700, Greg Brandt wrote:
Hey Gilles,
Thanks for the comments.
Would you be around to to keep maintaining to code?
Yes.
Out of curiousity, can it detect any kind of periodicity?
The goal of the algorithm is to decompose a time series with known
seasonality / periodicity into trend, seasonal, and remainder
components.
One could conceivably try many different parameters for seasonality,
then
use some objective function, probably involving residuals, to come up
with
the best value. But this would probably be considered an application
of STL.
There was a proposal to include "triple exponential smoothing", but
is
was deemed to be already an "application" rather than a general tool.
At
first sight, this code seems more in the line of CM. Am I right?
The goal of STL is very similar to the Holt Winters triple
exponential
smoothing method. So it may be the case that this falls into the
application category with respect to CM. There are a lot of tunable
parameters, and good values depend on data, so it's not so pure from
a
mathematical standpoint. However it definitely fills some void, as
this
algorithm ships with R. If CM isn't the right place for it, would you
know
of a good home?
Not really.
An idea (proposed some time ago) would be to have an "experimental"
package where such code could reside until we can make our mind...
Another (perhaps better) would be to have a "module" with this code.
Regards,
Gilles
Thanks,
-Greg
On Mon, Mar 21, 2016 at 3:53 AM, Gilles
<[email protected]>
wrote:
Hello.
On Thu, 17 Mar 2016 20:31:14 -0700, Greg Brandt wrote:
Hey Commons Math,
As part of some work on anomaly detection in time series data, a
couple
colleagues and I have put together a Java implementation of STL
<http://www.wessa.net/download/stl.pdf>, which we think might be
generally
useful.
It is based on commons-math3 LoessInterpolator
<
http://commons.apache.org/proper/commons-math/apidocs/org/apache/commons/math3/analysis/interpolation/LoessInterpolator.html
>,
so we thought it might be a natural contribution to the project.
Looks interesting (although I couldn't take the time to read the
paper).
The code currently lives here: https://github.com/brandtg/stl-java.
From
a
usability perspective, I think it needs some cleanup work, and it
needs
more thorough testing.
Would you be around to to keep maintaining to code?
However, an earlier variant of the code has run in production with
decent
results on reasonably large time series, so it is not too far off.
Out of curiousity, can it detect any kind of periodicity?
Is this something that would be valuable to Commons Math? A cursory
search
of JIRA and the mailing lists didn't turn up with anything, so my
apologies
if this has been previously discussed.
There was a proposal to include "triple exponential smoothing", but
is was
deemed to be already an "application" rather than a general tool.
At first sight, this code seems more in the line of CM. Am I
right?
Other committers' opinions requested...
Best regards,
Gilles
P.S. Please open a JIRA report ("Wish" type) so that we don't loose
track
in the flood of emails...
If so, I can massage the code to be consistent with the Developers
Guide,
simplify usage, and add more test coverage, then follow the
recommendations
there to create a patch.
Please feel free to submit pull requests or issues on the Github
repo in
addition to discussion on this thread.
Thanks,
-Greg
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
