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From: Daniel Winterstein <daniel@sodash.com>
Date: Mon, 16 May 2016 14:40:06 +0100
Message-ID: <CAEmLStmaE+=R9DJi1ubvYXMnWnrUeVyHQhYoAghm_nkKD_6NLA@mail.gmail.com>
Subject: [Math] Proposal: Add smoothing and fitting to the Kalman Filter
To: dev@commons.apache.org
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archived-at: Mon, 16 May 2016 13:40:57 -0000

Hello,

I was doing some work with Kalman Filters recently, and I noticed the
implementation in commons.math is missing a couple of features, namely
smoothing and model-fitting.

Would it be good to add these?

A little bit more on the model and the proposed features:
The Kalman Filter is a model for time-series data.
The version in commons.maths can do prediction (i.e. given the state
now, predict the next state).
The algorithm can also do smoothing (given a sequence of data, perhaps
with gaps, estimate the most likely state at each step) -- but this
version doesn't have an implementation.
Also, given a time-series dataset, you can fit a Kalman Filter. There
isn't a precise solution, but using expectation maximisation works
well.

I am new to the Apache Commons mailing list -- please forgive me if
this is the wrong way to go about things.

Kind regards,
 - Daniel

-- 
--------------------------------------
Dr Daniel Winterstein
Director
Edinburgh            +44 (0)772 5172 612
http://sodash.com   http://sogrow.co.uk

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