Remove k_endog & k_exog parameters in SSM

[Dekermanjian]

This PR is related to #589 and aims to remove redundant parameters k_endog and k_exog from SSM models. The following models will be updated:

• ETS Model
• SARIMAX Model
• VARMAX Model
• DFM Model
• Structural SSM API

In addition, this PR will also address

• VARMAX input validation functionality should be moved out to a helper #587

Closes #587
Closes #589

[Dekermanjian]

Hey @jessegrabowski, after updating all the models and the regression component in the structural api the complexity of the validation code dropped quite a bit. I am looking at pulling out that VARMAX validation utility to use across all the other models (SARIMAX, ETS, DFM) but the only commonality between them is how the endog_names are handled. I can pull out the validation for endog_names and wrap that up in a utility but that is only 4 lines of code. Do you think it is worth it? Never mind, I am going to do it. Once we have more models it will be worth it.

[jessegrabowski]

I was going to say yes anyway :D

[jessegrabowski]

I am looking at pulling out that VARMAX validation utility to use across all the other models

Mark that this PR will close both #589 and #587 as a result

[Dekermanjian]

Jesse, I marked the two open issues for closer upon merging this PR.

[jessegrabowski]

Nice work as always! Left some feedback.

Also rebase, we just merged the Pytensor update that will fix tests.

[jessegrabowski]

Change this to validate_names, and add a optional: bool =True argument so it can either error or return None. Then you can eliminate _get_state_names in the regression component and use this instead. Also can use it for the exog names in SARIMAX, etc.

[Dekermanjian]

I added a var_name argument as well so that if it does raise a value error the message will clearly state what variable is missing.