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I think there is one additional example that you could add to really complete this tutorial: how would you compute the pdf of the process model $p(x_k|x_{k-1})$. As a hands-on tutorial, that would be of huge benefit to people turning the priors, posteriors, and marginalized equations of particle filtering into working code. Making the assumption that the importance density $q$ is $p(x_k|x_{k-1})$ certainly makes computations of the weight update easier, but also makes it rather opaque to try any other importance density.
The text was updated successfully, but these errors were encountered:
I agree about the added value of such an example (it was one of the topic I excluded from the paper due to space limitations). I'd like to add it to the repository some day but unfortunately can't make promises on the timing.
I think there is one additional example that you could add to really complete this tutorial: how would you compute the pdf of the process model$p(x_k|x_{k-1})$ . As a hands-on tutorial, that would be of huge benefit to people turning the priors, posteriors, and marginalized equations of particle filtering into working code. Making the assumption that the importance density $q$ is $p(x_k|x_{k-1})$ certainly makes computations of the weight update easier, but also makes it rather opaque to try any other importance density.
The text was updated successfully, but these errors were encountered: