I understand from the README that it supports multiple covariates. And I understand I can make multiple models, one for each time series, from another GitHub issue here. Does it support multiple time series datasets, also known as multi-instance?
As a more concrete example, consider this OJ Sales Dataset. In this case, the data contains weekly sales of orange juice over 121 weeks. There are 3,991 stores included and three brands of orange juice per store so that 11,973 models can be trained.
I understand one can train independent models for each of the stores. However, I was interested in knowing if the package can take in data from multiple stores to learn correlations between them.
I understand from the README that it supports multiple covariates. And I understand I can make multiple models, one for each time series, from another GitHub issue here. Does it support multiple time series datasets, also known as multi-instance?
As a more concrete example, consider this OJ Sales Dataset. In this case, the data contains weekly sales of orange juice over 121 weeks. There are 3,991 stores included and three brands of orange juice per store so that 11,973 models can be trained.
I understand one can train independent models for each of the stores. However, I was interested in knowing if the package can take in data from multiple stores to learn correlations between them.