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'¶ “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