Posts tagged hidden markov model

Hidden Markov Models in PyMC: marginalize and recover a DiscreteMarkovChain

A hidden Markov model (HMM) describes a system that moves through a sequence of hidden discrete states, where each state emits a noisy observation. We never see the states directly; we only see the emissions, and we want to reason backward to the states that most likely produced them.

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How to wrap a JAX function for use in PyMC

This notebook uses libraries that are not PyMC dependencies and therefore need to be installed specifically to run this notebook. Open the dropdown below for extra guidance.

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