statsmodels.tsa.vector_ar.svar_model.SVAR.fit

SVAR.fit(A_guess=None, B_guess=None, maxlags=None, method='ols', ic=None, trend='c', verbose=False, s_method='mle', solver='bfgs', override=False, maxiter=500, maxfun=500)[source]

Fit the SVAR model and solve for structural parameters

Parameters:

  • A_guess (array_like, optional) – A vector of starting values for all parameters to be estimated in A.

  • B_guess (array_like, optional) – A vector of starting values for all parameters to be estimated in B.

  • maxlags (int) – Maximum number of lags to check for order selection, defaults to 12 * (nobs/100.)**(1./4), see select_order function

  • method ({'ols'}) – Estimation method to use

  • ic ({'aic', 'fpe', 'hqic', 'bic', None}) – Information criterion to use for VAR order selection. aic : Akaike fpe : Final prediction error hqic : Hannan-Quinn bic : Bayesian a.k.a. Schwarz

  • verbose (bool, default False) – Print order selection output to the screen

  • trend – “c” - add constant “ct” - constant and trend “ctt” - constant, linear and quadratic trend “n” - co constant, no trend Note that these are prepended to the columns of the dataset.

  • {"c" (str) – “c” - add constant “ct” - constant and trend “ctt” - constant, linear and quadratic trend “n” - co constant, no trend Note that these are prepended to the columns of the dataset.

  • "ct" – “c” - add constant “ct” - constant and trend “ctt” - constant, linear and quadratic trend “n” - co constant, no trend Note that these are prepended to the columns of the dataset.

  • "ctt" – “c” - add constant “ct” - constant and trend “ctt” - constant, linear and quadratic trend “n” - co constant, no trend Note that these are prepended to the columns of the dataset.

  • "n"} – “c” - add constant “ct” - constant and trend “ctt” - constant, linear and quadratic trend “n” - co constant, no trend Note that these are prepended to the columns of the dataset.

  • s_method ({'mle'}) – Estimation method for structural parameters

  • solver ({'nm', 'newton', 'bfgs', 'cg', 'ncg', 'powell'}) – Solution method See statsmodels.base for details

  • override (bool, default False) – If True, returns estimates of A and B without checking order or rank condition

  • maxiter (int, default 500) – Number of iterations to perform in solution method

  • maxfun (int) – Number of function evaluations to perform

Notes

Lütkepohl pp. 146-153 Hamilton pp. 324-336

Returns:

est

Return type:

SVARResults