Posts by Juan Orduz

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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Modeling Heteroscedasticity with BART

In this notebook we show how to use BART to model heteroscedasticity as described in Section 4.1 of pymc-bart’s paper [Quiroga et al., 2022]. We use the marketing data set provided by the R package datarium [Kassambara, 2019]. The idea is to model a marketing channel contribution to sales as a function of budget.

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