pyuncertainnumber.pba.dependency
================================

.. py:module:: pyuncertainnumber.pba.dependency


Classes
-------

.. autoapisummary::

   pyuncertainnumber.pba.dependency.Dependency


Functions
---------

.. autoapisummary::

   pyuncertainnumber.pba.dependency.supported_family_check
   pyuncertainnumber.pba.dependency.empirical_copula
   pyuncertainnumber.pba.dependency.pl_3d_copula


Module Contents
---------------

.. py:class:: Dependency(family: str, params: numbers.Number | None = None, **kwargs)

   Dependency class to specify copula models.

   :param family: Name of the copula family, one of
                  "gaussian", "t", "frank", "gumbel", "clayton", "independence".
   :type family: str
   :param params: Backward-compatible single-parameter shortcut:
                  - gaussian/t: interpreted as corr
                  - frank/gumbel/clayton: interpreted as theta
                  - independence: ignored
   :type params: Number | None
   :param \*\*kwargs: Any keyword parameters supported by the selected copula,
                      e.g. corr=..., df=..., theta=..., k_dim=..., allow_singular=...

   .. rubric:: Examples

   >>> Dependency("gaussian", params=0.8, k_dim=3)          # legacy style
   >>> Dependency("gaussian", corr=0.8, k_dim=3)            # explicit
   >>> Dependency("t", corr=0.6, df=5, k_dim=4)
   >>> Dependency("frank", theta=2.5, k_dim=2)
   >>> Dependency("independence", k_dim=5)


   .. py:attribute:: copulas_dict


   .. py:attribute:: _single_param_alias


   .. py:attribute:: family
      :value: ''



   .. py:attribute:: params
      :value: None



   .. py:attribute:: _copula


   .. py:property:: copula

      Access the underlying statsmodels copula instance.


   .. py:method:: _post_init_check()


   .. py:method:: __repr__()


   .. py:method:: pdf(u)


   .. py:method:: cdf(u)


   .. py:method:: u_sample(n: int, random_state=None)

      draws n samples in the U space (unit hypercube)



   .. py:method:: display(style='3d_cdf', ax=None)

      show the PDF or CDF in the u space



   .. py:method:: fit(data)


.. py:function:: supported_family_check(c)

   check if copula family is supported


.. py:function:: empirical_copula(data)

   compute the empirical copula


.. py:function:: pl_3d_copula(U, V, Z)