Dynamic predictions multi state model with time dependent covariates

I need to make dynamic predictions of the time of assembly of machines.

Since I want to update forecast when parts of the machine have been made, I need multi-state models.

Since I have time dependent covariates, such as the number of missing parts required to make the machine, I think I have 2 options: time dependent Cox regression or joint model of longitudinal and multi-state model.

Unfortunately I have not found any R package that allow to make dynamic predictions with these models.

For example JMBayes/JMBayes2 doesn’t allow dynamic predictions from multistate model

Mstate + Cox doesn’t allow combining time varying covariates with multi-state models

Do you know any R packages that can help me or suggestions on how I can fit these models and use them to make predictions?

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You might try pomp—which stands for Partially Observed Markov Processes. I used this package for a state-space model in my DTAT paper, and found it a wonderful way to gain access to advanced methods within the data assimilation sphere. The documentation is excellent, too.

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