skimpy.inference.parameters
===========================

.. py:module:: skimpy.inference.parameters


Attributes
----------

.. autoapisummary::

   skimpy.inference.parameters.EPSILON


Classes
-------

.. autoapisummary::

   skimpy.inference.parameters.SecureMultivariateNormal
   skimpy.inference.parameters.LogNormalPriorParameterDistribution
   skimpy.inference.parameters.PosteriorLogNormalParameterPopulation
   skimpy.inference.parameters.PosteriorNormalParameterPopulation


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

.. py:data:: EPSILON
   :value: 1e-09


.. py:class:: SecureMultivariateNormal(mu, sigma, var)

   Bases: :py:obj:`object`


   .. py:attribute:: variable_parameters


   .. py:attribute:: constant_parameters


   .. py:attribute:: mu


   .. py:attribute:: variable_index


   .. py:attribute:: const_index


   .. py:attribute:: _dist


   .. py:method:: rvs(size, random_state=None)


.. py:class:: LogNormalPriorParameterDistribution

   TF Based model


.. py:class:: PosteriorLogNormalParameterPopulation(parameter_poulations, likelyhoods=None)

   Bases: :py:obj:`object`


       


   .. py:attribute:: mu
      :value: []



   .. py:attribute:: sigma
      :value: []



   .. py:attribute:: pdf
      :value: []



   .. py:attribute:: cum_weights


   .. py:method:: resample(N, seed=None)


.. py:class:: PosteriorNormalParameterPopulation(parameter_poulations, likelyhoods=None)

   Bases: :py:obj:`object`


       


   .. py:attribute:: mu
      :value: []



   .. py:attribute:: sigma
      :value: []



   .. py:attribute:: pdf
      :value: []



   .. py:attribute:: cum_weights


   .. py:method:: resample(N, seed=None)