Re: [Bayes++] Bayes++ EKF Example Request

[Nithya N. V. <nvi...@cs...>]

Hi Nicola, Michael,

thank you very much for your reply. It really helped!
-Nithya

On Sun, 6 Aug 2006, Michael Stevens wrote:

> Date: Sun, 6 Aug 2006 21:50:01 +0200
> From: Michael Stevens <ma...@mi...>
> To: Nithya Nirmal Vijayakumar <nvi...@cs...>
> Subject: Re: Bayes++ EKF Example Request
> 
> Hi Hithya,
>
> Sorry to be so late in replying. I am horribly busy at the moment!
>
> You at the PV (Position Velocity) filter example, is actually very close to
> waht you need.
>
> The PV example uses an Unscented filter which is closely related to an
> Extended Kalman filter. If you wish to use an Extended Kalman filter the code
> can be trivially changed to use the 'Covariance_scheme'.
>
> In the PV example the data points of the time series are the position of a
> moving object. The filter estimates the object velocity using a motion model
> and can predict future positions and velocities. The estimator fuses it own
> predictions with noisy obserations to give a best estimate given the model.
>
> In your question you say.
>> and fill in any missing values.
>
> This makes me wonder if require and iterative estimate such as the Kalman
> filter for you problem. If you have all the know data points of time series a
> priori and wish to determine estimates of data points at any time then what
> you require is a batch smoother. Sadly Bayes++ does not have any smoothers
> they are a topic in themselves!!
>
> Hopes this helps a bit,
>
> Michael
>
> -- 
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>                 Bayesian Filtering
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