EM algorithm convergence KF log likelihood decrease

AI Thread Summary
The discussion centers on the issue of decreasing log likelihood in a Kalman Filter (KF) implementation while using the Expectation-Maximization (EM) algorithm to estimate model parameters. The original poster questions whether this decrease indicates a problem with their implementation or if it is a common occurrence. A suggestion is made to reference code from repositories like the R platform to compare results. The conversation highlights the importance of verifying implementation against established examples to troubleshoot potential issues. Overall, the decrease in log likelihood may not necessarily indicate an error but warrants further investigation.
MikeLowri123
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Hi everyone,

Im running the KF to learn parameters of a model, the log likelihood of the p(Y_{k}|Y_{k-1}), however decreases.

Can anyone advise, does this mean my implementation is wrong or can this just be the case.

Advice appreciated

Thanks
 
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Can anyone offer a small piece of advice or even a reference??
 
Hey MikeLowri123.

If you are using the EM to fit some parameters for a parametric distribution, have you tried grabbing some code from a repository like the R platform and seeing the results?
 

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