The Estimate Method

The estimate() method runs an estimation of coefficients on basis of a given specification.

Input:

specification

- an instance of class EquationSpecification specifying variables to be used in the estimation.

dataset

- a Dataset representing the whole set of observations.

outcome_attribute

- a character string determining the dependent variable (a fully qualified name).

index

- an index within the dataset determining which observations will be used for the estimation. If it is not given, the whole dataset is considered.

procedure

- a character string giving the fully qualified name of the estimation procedure (see Section 24.5.6). This argument can be also passed via estimate_config as an entry 'estimation'. The default value is None.

data_objects

- a dictionary containing additional datasets needed for computing variables. This argument is obsolete - the datasets should be included in the dataset_pool argument of the constructor.

estimate_config

- additional Resources (or dictionary) for controlling the estimation run.

Algorithm: 
In addition to index, the number of dataset members entering the estimation can be controlled by an entry 'estimation_size_agents' in estimate_config which should have a value between 0 and $1$ . It gives the portion of index that will be used in the estimation. If it is less than 1, the indices are randomly sampled.

The method invokes computation of variables given in the specification as well as of the outcome attribute. For each submodel, it creates the corresponding data matrix and invokes the run() method of the module given by the argument procedure, passing data, the class attribute regression and estimate_config (after adding entries needed for the estimation) as arguments (see Section 24.5.6 for more details). From the returned dictionary, items ``estimators'', ``standard_errors'', ``other_measures'' and ``other_info'' are extracted. After results from all submodels are collected, a Coefficient object is created using those extracted values.

Output: 
The method returns a tuple of the created Coefficient object and a dictionary with one entry for each submodel. Each entry is a dictionary returned by estimation procedure for that submodel.