FittedVAR¶
FittedVAR — reduced-form posterior from Bayesian VAR estimation.
FittedVAR
¶
Bases: ImpulsoBaseModel
Immutable container for a fitted (reduced-form) Bayesian VAR.
Attributes:
| Name | Type | Description |
|---|---|---|
idata |
InferenceData
|
ArviZ InferenceData with posterior draws. |
n_lags |
int
|
Lag order used in estimation. |
data |
VARData
|
Original VARData used for fitting. |
var_names |
list[str]
|
Names of endogenous variables. |
volatility |
VolatilityProcess
|
Volatility process used at fit time. Required; populated by VAR.fit from VAR.volatility (default at the spec level is "constant", which resolves to Constant()). |
coefficients
property
¶
Posterior draws of B coefficient matrices.
has_exog
property
¶
Whether the model includes exogenous variables.
intercepts
property
¶
Posterior draws of intercept vectors.
forecast(steps, exog_future=None)
¶
Produce h-step-ahead forecasts from the reduced-form posterior.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
steps
|
int
|
Number of forecast steps. |
required |
exog_future
|
ndarray | None
|
Future exogenous values, shape (steps, k). Required if model has exog. |
None
|
Returns:
| Type | Description |
|---|---|
ForecastResult
|
ForecastResult with posterior forecast draws. |
set_identification_strategy(scheme)
¶
Apply a structural identification scheme.
Queries the fitted volatility process for the Cholesky factor of Σ
and passes it to the scheme. For constant volatility, the factor is
the same across all time points; for stochastic volatility (P3),
cholesky_at(t=None) returns the most-recent slice and
downstream IRF/FEVD/HD methods can re-query at other at values.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
scheme
|
IdentificationScheme
|
An IdentificationScheme protocol instance (e.g. Cholesky, SignRestriction). |
required |
Returns:
| Type | Description |
|---|---|
IdentifiedVAR
|
IdentifiedVAR with structural_shock_matrix in the posterior. |
sigma()
¶
Posterior draws of the structural-shock covariance Σ.
Dispatches to the configured volatility adapter so the returned shape depends on whether Σ is time-invariant or time-varying:
- Constant volatility — Σ is shared across time, so the result
has shape
(chains, draws, n_vars, n_vars). - Stochastic volatility — Σ_t evolves, so the result has shape
(chains, draws, T, n_vars, n_vars)whereTis the in-sample length after lag trimming. Callers needing a single slice should callvolatility.cholesky_at(posterior, t)and square the factor themselves.
Note
Breaking change vs. v0.0.4 and earlier: sigma is now
a method, not a property. Call sites that used fitted.sigma
must be updated to fitted.sigma().
Returns:
| Type | Description |
|---|---|
ndarray
|
Posterior draws of Σ (or Σ_t for SV) computed from the |
ndarray
|
volatility adapter's Cholesky factor as |