leaspy.variables.utilities
==========================

.. py:module:: leaspy.variables.utilities


Functions
---------

.. autoapisummary::

   leaspy.variables.utilities.compute_individual_parameter_std_from_sufficient_statistics


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

.. py:function:: compute_individual_parameter_std_from_sufficient_statistics(state, individual_parameter_values, individual_parameter_sqr_values, *, individual_parameter_name, dim, **kws)

   
   Maximization rule, from the sufficient statistics, of the standard-deviation of Gaussian prior for individual latent variables.


   :Parameters:

       **state** : :obj:`dict`[:obj:`str`, :class:`torch.Tensor`]
           The current state object that holds all the variables

       **individual_parameter_values** : :class:`torch.Tensor`
           Tensor containing individual parameter values, used to compute current means.

       **individual_parameter_sqr_values** : :class:`torch.Tensor`
           Tensor containing squared individual parameter values, used to compute variances.

       **individual_parameter_name** : :obj:`str`
           The name of the individual parameter for which to compute the std.

       **dim** : :obj:`int`
           The dimension along which to compute the mean and variance



   :Returns:

       :class:`torch.Tensor`
           The updated standard deviation of the Gaussian prior for the individual parameter











   ..
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