.. _fwflag_multir:
=========
--multir
=========
Switch
======

--multir

Description
===========

Multivariate regression: regresses each feature on all requested outcomes simultaneously (one model per feature, all outcomes as predictors — the reverse direction of :doc:`fwflag_correlate`, which fits one model per outcome/feature pair).

Argument and Default Value
==========================

No argument. Boolean switch, default: ``False``.

Details
=======

Calls ``oa.multRegressionWithFeatures(fg, spearman, p_correction_method, blacklist, whitelist, showfeatfreqs, outcomeWithOutcome, interactions=args.interactions)``. This is the switch :doc:`fwflag_interactions` requires — without ``--multir``, ``--interactions`` has no effect. With :doc:`fwflag_csv`, writes results via ``oa.writeSignificantCoeffs4dVis()`` to a ``..multiprint..`` file for use with 4dVis-style visualization, using :doc:`fwflag_output_name`/``--output_dir`` the same way as other correlate-family output.

Other Switches
==============

Required Switches:

* :doc:`fwflag_d`, :doc:`fwflag_c`, :doc:`fwflag_t`
* :doc:`fwflag_f`
* :doc:`fwflag_outcome_table`, :doc:`fwflag_outcomes`

Optional Switches:

* :doc:`fwflag_interactions`
* :doc:`fwflag_csv`

Example Commands
================

.. code-block:: bash

	dlatkInterface.py -d dla_tutorial -t msgs -c user_id -f 'feat$1gram$msgs$user_id$16to16' \
	--outcome_table blog_outcomes --outcomes age gender --multir --interactions --csv --output_name ./multir_out