.. _Generalized score with marginal likelihood:

Generalized score with marginal likelihood
=============================================

Generalized score with marginal likelihood for single dimensional variables
---------------------------------------------------------------------------
Calculate the local score by negative marginal likelihood, based on a regression model in RKHS [1]_.

Usage
^^^^^^^
.. code-block:: python

    from causallearn.score.LocalScoreFunction import local_score_marginal_general
    score = local_score_marginal_general(Data, Xi, PAi, parameters)

Parameters
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
**Data**: (sample, features).

**Xi**: current index.

**PAi**: parent indexes.

**parameters**: None.

Returns
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
**score**: Local score.


Generalized score with marginal likelihood for multi-dimensional variables
------------------------------------------------------------------------------
Calculate the local score by negative marginal likelihood, based on a regression model in RKHS
for data with multi-dimensional variables [1]_.

Usage
^^^^^^^
.. code-block:: python

    from causallearn.score.LocalScoreFunction import local_score_marginal_multi
    score = local_score_marginal_multi(Data, Xi, PAi, parameters)

Parameters
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
**Data**: (sample, features).

**Xi**: current index.

**PAi**: parent indexes.

**parameters**:
               - dlabel: indicate the data dimensions that belong to each variable. It is only used when the variables have multivariate dimensions.

Returns
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
**score**: Local score.

.. [1] Huang, B., Zhang, K., Lin, Y., Schölkopf, B., & Glymour, C. (2018, July). Generalized score functions for causal discovery. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 1551-1560).