Autoregressive.covariance_matrix_solve(expval, index, stdev, rhs)
[source]
Solves matrix equations of the form covmat * soln = rhs
and returns the values of soln
, where covmat
is the covariance matrix represented by this class.
Parameters: 


Returns: 
soln – The solutions to the matrix equations. 
Return type: 
list/tuple of arraylike 
Returns None if the solver fails.
Some dependence structures do not use expval
and/or index
to determine the correlation matrix. Some families (e.g. binomial) do not use the stdev
parameter when forming the covariance matrix.
If the covariance matrix is singular or not SPD, it is projected to the nearest such matrix. These projection events are recorded in the fit_history member of the GEE model.
Systems of linear equations with the covariance matrix as the left hand side (LHS) are solved for different right hand sides (RHS); the LHS is only factorized once to save time.
This is a default implementation, it can be reimplemented in subclasses to optimize the linear algebra according to the struture of the covariance matrix.
© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.genmod.cov_struct.Autoregressive.covariance_matrix_solve.html