How the User Inputs are Processed

Model Processing

process_model(model_dict)[source]

Check, clean, extend and transform the model specs.

Check the completeness, consistency and validity of the model specifications.

Set default values and extend the model specification where necessary.

Parameters

model_dict (dict) – The model specification. See: Model specifications

Returns

dict – nested dictionary of model specs. It has the following entries: - dimensions (dict): Dimensional information like n_states, n_periods, n_controls, n_mixtures. See dimensions. - labels (dict): Dict of lists with labels for the model quantities like factors, periods, controls, stagemap and stages. See labels - anchoring (dict): Information about anchoring. See anchoring - transition_functions (tuple): Tuple of tuples of length n_periods. Each inner tuple has the following two entries: (name_of_transition_function, callable). - update_info (pandas.DataFrame): DataFrame with one row per Kalman update needed in the likelihood function. See update_info. - normalizations (dict): Nested dictionary with information on normalized factor loadings and intercepts for each factor. See normalizations.

get_dimensions(model_dict)[source]

Extract the dimensions of the model.

Parameters

model_dict (dict) – The model specification. See: Model specifications

Returns

dict –

Dimensional information like n_states, n_periods, n_controls,

n_mixtures. See dimensions.

fill_list(short_list, fill_value, length)[source]

Extend a list to specified length by filling it with the fill_value.

Examples: >>> fill_list([“a”], “b”, 3) [‘a’, ‘b’, ‘b’]

Data Processing

process_data_for_estimation(df, labels, update_info, anchoring_info)[source]

Process the data for estimation.

Parameters

  • df (DataFrame) – panel dataset in long format. It has a MultiIndex where the first level indicates the period and the second the individual.

  • labels (dict) – Dict of lists with labels for the model quantities like factors, periods, controls, stagemap and stages. See labels

  • update_info (pandas.DataFrame) – DataFrame with one row per Kalman update needed in the likelihood function. See update_info.

  • anchoring_info (dict) – Information about anchoring. See anchoring

Returns

meas_data (jax.numpy.array) –

Array of shape (n_updates, n_obs) with data on

observed measurements. NaN if the measurement was not observed.

control_data (jax.numpy.array): Array of shape (n_periods, n_obs, n_controls)

with observed control variables for the measurement equations.

Model Checking

check_model(model_dict, labels, dimensions, anchoring)[source]

Check consistency and validity of the model specification.

labels, dimensions and anchoring information are done before the model checking because processing them will not raise any errors except for easy to understand KeyErrors.

Other specifications are checked in the model dict before processing to make sure that the assumptions we make during the processing are fulfilled.

Parameters

  • model_dict (dict) – The model specification. See: Model specifications

  • dimensions (dict) – Dimensional information like n_states, n_periods, n_controls, n_mixtures. See dimensions.

  • labels (dict) – Dict of lists with labels for the model quantities like factors, periods, controls, stagemap and stages. See labels

  • anchoring (dict) – Dictionary with information about anchoring. See anchoring

Raises

ValueError –

Reference Guides Modules Related to Estimation