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Hidden Markov Modeling of Continuous Time Longitudinal Data in R

We have a hidden Markov Model with state diagram X1->X2->X3->X4->X5. There is no chance of going back to the previous state. We are having trouble implementing this in R using artifical data and would like some advice. You must have had at least several projects completed in working with HMM's (preferably in R). You must also be able to make recommendations. For instance, is our model too simple? Do we need to incorporate covariates if any? Right now, we are getting an error message, possibly related to the input matrices. If you can't fix the error message (or figure out the source), please do not apply. Of course, fixing it is not the totality of the project, but is very important. Attached is our data set of observations.

Skills: R Programming Language, Statistics, Statistical Analysis, Statistical Modeling

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