4.8.1.2.6. statsmodels.tsa.api.SVAR¶
-
class
statsmodels.tsa.api.
SVAR
(endog, svar_type, dates=None, freq=None, A=None, B=None, missing='none')[source]¶ Fit VAR and then estimate structural components of A and B, defined:
\[Ay_t = A_1 y_{t-1} + \ldots + A_p y_{t-p} + B\]ar(epsilon_t)
Parameters: endog : array-like
1-d endogenous response variable. The independent variable.
- dates : array-like
must match number of rows of endog
- svar_type : str
“A” - estimate structural parameters of A matrix, B assumed = I “B” - estimate structural parameters of B matrix, A assumed = I “AB” - estimate structural parameters indicated in both A and B matrix
- A : array-like
neqs x neqs with unknown parameters marked with ‘E’ for estimate
- B : array-like
neqs x neqs with unknown parameters marked with ‘E’ for estimate
4.8.1.2.6.1. Methods¶
__init__ (endog, svar_type[, dates, freq, A, ...]) |
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check_order (J) |
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check_rank (J) |
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fit ([A_guess, B_guess, maxlags, method, ic, ...]) |
Fit the SVAR model and solve for structural parameters |
from_formula (formula, data[, subset]) |
Create a Model from a formula and dataframe. |
hessian (AB_mask) |
Returns numerical hessian. |
information (params) |
Fisher information matrix of model |
initialize () |
Initialize (possibly re-initialize) a Model instance. |
loglike (params) |
Loglikelihood for SVAR model |
predict (params[, exog]) |
After a model has been fit predict returns the fitted values. |
score (AB_mask) |
Return the gradient of the loglike at AB_mask. |
4.8.1.2.6.2. Attributes¶
endog_names |
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exog_names |