[Unit Test Extension]: Implement "default setting unit tests"

In the python package `DoubleML`, we do have unit tests for model defaults, see https://github.com/DoubleML/doubleml-for-py/blob/master/doubleml/tests/test_doubleml_model_defaults.py. The intention behind such "default setting unit tests" is twofold:

1. It should assert that the defaults are valid / meaningful, i.e., the code runs through successfully with default values for the input parameters.
2. The unit tests serve as a reminder to update the documentation of defaults in case a default value is being changed.

Such "default setting unit tests" could be done for the initialization of the model classes as well as for the most important methods.

Note: Such "default setting unit tests" would have been sensitive for bugs like #155 & #156

Start by reading the referenced Python test file, doubleml/tests/test_doubleml_model_defaults.py, then locate the corresponding model initializers and important methods in the R package. Done means default-setting tests cover the agreed model classes and methods, verify that defaults run successfully, and help keep documented defaults current.

Written by the indexing model from the issue text.