statsmodels.tsa.vector_ar.vecm.select_order¶
-
statsmodels.tsa.vector_ar.vecm.select_order(data, maxlags, deterministic=
'n'
, seasons=0
, exog=None
, exog_coint=None
)[source]¶ Compute lag order selections based on each of the available information criteria.
- Parameters:¶
- dataarray_like (
nobs_tot
x
neqs
) The observed data.
- maxlags
int
All orders until maxlag will be compared according to the information criteria listed in the Results-section of this docstring.
- deterministic
str
{“n”, “co”, “ci”, “lo”, “li”} "n"
- no deterministic terms"co"
- constant outside the cointegration relation"ci"
- constant within the cointegration relation"lo"
- linear trend outside the cointegration relation"li"
- linear trend within the cointegration relation
Combinations of these are possible (e.g.
"cili"
or"colo"
for linear trend with intercept). See the docstring of theVECM
-class for more information.- seasons
int
, default: 0 Number of periods in a seasonal cycle.
- exog
ndarray
(nobs_tot
x
neqs
)or
None, default: None Deterministic terms outside the cointegration relation.
- exog_coint
ndarray
(nobs_tot
x
neqs
)or
None, default: None Deterministic terms inside the cointegration relation.
- dataarray_like (
- Returns:¶
- selected_orders
statsmodels.tsa.vector_ar.var_model.LagOrderResults
- selected_orders