Intricate, they weave,
Complex models, they conceive,
Chance's web they leave.
--ChatGPT
7. Probabilistic models: from simple to complex#
In this chapter, we take a deeper look at probabilistic models, which we have already encountered throughout.
This chapter has three main objectives:
To show how to construct a variety of probabilistic models, in particular by using the notion of conditional independence.
To describe methods for estimating parameters and hidden states, as well as for sampling.
To discuss and implement some applications, including kalman filtering and gibbs sampling.
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