Allow for observed factors

[janosg]

Current situation

There are only latent factors. Observed controls can only enter the measurement equations.

Desired situation

Observed variables can enter the transition equation.

Why not just fix parameters

There are a few important conceptual differences between observed factors and "fake latent factors" that have just one measurement with fixed loading and intercept in each period.

• It is not necessary to estimate transition equations for observed factors
• Observed factors should not enter the covariance matrix of the states
• Observed factors do not need transition shocks
• The number of sigma points only needs to grow in latent factors and not in observed factors.

User interface

The model dictionary now can contain an entry called "observed_factors" which is simply a list with variable names in the empirical dataset. Those variables cannot contain missings. The set of observed factors is assumed to be same in all periods. If that is not wanted, coefficients can be fixed to zero.

The observed factors will enter the right hand side of transition equations in exactly the same way as latent factors. However, they do not have their own transition equations.

To-Do

• [x] model["labels"] needs to contain "latent_factors", "observed_factors" and "all_factors" instead of just factors
• [x] all functions that used model["labels"]["factors"] now needs to use the correct one of the three factor entries
• [x] Adjust parse_params, params_index and constraints
• [x] Adjust process_data
• [x] Adjust sigma points creation
• [x] Adjust predict step
• [x] Adjust visualize_transition_equations
• [ ] Adjust simulate_dataset

[codecov-commenter]

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