Re: [Bayes++] Code issues

[Michael S. <ma...@mi...>]

On Mittwoch 21 September 2005 00:09, you wrote:
> Great work! :)
>
> I have also been unable to find a method for generating samples from the
> models. It would have been great to be able to get samples with desired
> covariance, based on prediction- and observation models. Typical usage
> would be to simulate a process, and to generate observations from it.

There is a Gaussian sampler as a helper class for in the SIR filter. In 
"SIRFlt.hpp" I define the class template 'Sampled_general_predict_model'
and the two predefine classes 'Sampled_LiAd_predict_model' 
'Sampled_LiInAd_predict_model'.

These convert Linear or Linrz predict models into 'Sampled_predict' models. 
You define the Gaussian covaiance by the values of G and q in the predict 
model. This is much the same as your 'SampleCorelated' function. Except I 
think I have the spelling correct in this case :-)

In the case of observation models Bayes++ has model generalisers in 
"models.hpp". For example 'General_LiUnAd_observe_model' generalises a Linear 
Uncorrelated Addative noise observe model. The generalised model is also a 
'Likelihood_observe_model' and so the likelihood of a state given an 
obervation can be computed with the 'L' function. This allows you to use a 
Gaussian noise models to resample, for example in the 'SIR_scheme'.

Best regard, and thanks for the feedback,
	Michael
-- 
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Michael Stevens Systems Engineering

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Navigation Systems, Estimation  and
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