I want to use some python library to create a PGM for joint-distribution modeling and probabilistic inference. To be more specific, I have a time series data, which consists of many time slices. There are multiple variables in each time slices. Some of the variables are discrete, others are continuous. I want to do structure learning and parameter learning with this data and finally create a PGM. But I couldn’t find any suitable python library for that.
I found a library named PyPGM,

But it seems that it doesn’t support time series and hybrid(discrete and continuous)I want to use some python library to create a PGM for joint-distribution modeling and probabilistic inference. To be more specific, I have a time series data, which consists of many time slices. There are multiple variables in each time slices. Some of the variables are discrete, others are continuous. I want to do structure learning and parameter learning with this data and finally create a PGM. But I couldn’t find any suitable python library for that.
I found a library named PyPGM,

But it seems that it doesn’t support time series and hybrid(discrete and continuous) I want to use some python library to create a PGM for joint-distribution modeling and probabilistic inference. To be more specific, I have a time series data, which consists of many time slices. There are multiple variables in each time slices. Some of the variables are discrete, others are continuous. I want to do structure learning and parameter learning with this data and finally create a PGM. But I couldn’t find any suitable python library for that.
I found a library named PyPGM,

But it seems that it doesn’t support time series and hybrid(discrete and continuous) python MATLAB Answers — New Questions

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