statsmodels.tsa.vector_ar.var_model.VAR.fit¶
-
VAR.fit(maxlags=
None
, method='ols'
, ic=None
, trend='c'
, verbose=False
)[source]¶ Fit the VAR model
- Parameters:¶
- maxlags{
int
,None
},default
None
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
- verbosebool,
default
False
Print order selection output to the screen
- trend
str
{“c”, “ct”, “ctt”, “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.
- maxlags{
- Returns:¶
VARResults
Estimation results
Notes
See Lütkepohl pp. 146-153 for implementation details.
Last update:
Dec 16, 2024