Implements a Hidden Markov Model (HMM) with a random trip effect to estimate the distribution of travel time. The HMM is used to capture dependency on hidden congestion states. The trip effect is used to capture dependency on driver behaviour. Variations of those two types of dependencies leads to four models to estimate the distribution of travel time. Prediction methods for each model is provided.
|Maintainer||Mohamad Elmasri <firstname.lastname@example.org>|
|Package repository||View on GitHub|
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