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.

data_objects

- a dictionary containing other datasets and arguments needed for computing variables.

estimate_config

- additional Resources for controlling the estimation run.

Algorithm: 
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 6.5.6 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 entries for each submodel equals a dictionary returned by the run() method of procedure for that submodel.