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Found 3 papers, 1 papers with code
Time Series Analysis and Modeling to Forecast: a Survey
Time series decomposition is a major preprocessing task, to separate nonstationary effects (the deterministic components) from the remaining stochastic constituent, assumed to be stationary.
Partially Hidden Markov Chain Linear Autoregressive model: inference and forecasting
For discrete-valued regimes, some models such as the popular Hidden Markov Chain (HMC) describe time series whose state process is unknown at all time-steps.
A Survey on Latent Tree Models and Applications
In data analysis, latent variables play a central role because they help provide powerful insights into a wide variety of phenomena, ranging from biological to human sciences.
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