class statsmodels.sandbox.sysreg.SUR(sys, sigma=None, dfk=None)
[source]
Seemingly Unrelated Regression
Parameters: |
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cholsigmainv
array – The transpose of the Cholesky decomposition of pinv_wexog
df_model
array – Model degrees of freedom of each equation. p_{m} - 1 where p is the number of regressors for each equation m and one is subtracted for the constant.
df_resid
array – Residual degrees of freedom of each equation. Number of observations less the number of parameters.
endog
array – The LHS variables for each equation in the system. It is a M x nobs array where M is the number of equations.
exog
array – The RHS variable for each equation in the system. It is a nobs x sum(p_{m}) array. Which is just each RHS array stacked next to each other in columns.
history
dict – Contains the history of fitting the model. Probably not of interest if the model is fit with igls
= False.
iterations
int – The number of iterations until convergence if the model is fit iteratively.
nobs
float – The number of observations of the equations.
normalized_cov_params
array – sum(p_{m}) x sum(p_{m}) array \(\left[X^{T}\left(\Sigma^{-1}\otimes\boldsymbol{I}\right)X\right]^{-1}\)
pinv_wexog
array – The pseudo-inverse of the wexog
sigma
array – M x M covariance matrix of the cross-equation disturbances. See notes.
sp_exog
CSR sparse matrix – Contains a block diagonal sparse matrix of the design so that exog1 … exogM are on the diagonal.
wendog
array – M * nobs x 1 array of the endogenous variables whitened by cholsigmainv
and stacked into a single column.
wexog
array – M*nobs x sum(p_{m}) array of the whitened exogenous variables.
All individual equations are assumed to be well-behaved, homoeskedastic iid errors. This is basically an extension of GLS, using sparse matrices.
Zellner (1962), Greene (2003)
fit ([igls, tol, maxiter]) | igls : bool Iterate until estimates converge if sigma is None instead of two-step GLS, which is the default is sigma is None. |
initialize () | |
predict (design) | |
whiten (X) | SUR whiten method. |
© 2009–2012 Statsmodels Developers
© 2006–2008 Scipy Developers
© 2006 Jonathan E. Taylor
Licensed under the 3-clause BSD License.
http://www.statsmodels.org/stable/generated/statsmodels.sandbox.sysreg.SUR.html