Priors¶
Prior specifications for VAR models.
MinnesotaPrior
¶
Bases: BaseModel
Minnesota prior for VAR coefficient shrinkage.
Attributes:
| Name | Type | Description |
|---|---|---|
tightness |
float
|
Overall shrinkage toward prior mean. Must be > 0. |
decay |
Literal['harmonic', 'geometric']
|
How coefficients shrink on longer lags. |
cross_shrinkage |
float
|
Shrinkage on other variables' lags vs own. 0 = only own lags, 1 = equal. |
build_priors(n_vars, n_lags)
¶
Build prior mean and standard deviation arrays for VAR coefficients.
Parameters:
| Name | Type | Description | Default |
|---|---|---|---|
n_vars
|
int
|
Number of endogenous variables. |
required |
n_lags
|
int
|
Number of lags. |
required |
Returns:
| Type | Description |
|---|---|
dict
|
Dictionary with keys 'B_mu' and 'B_sigma' as numpy arrays. |