statsmodels.tsa.vector_ar.var_model.VAR¶

class statsmodels.tsa.vector_ar.var_model.VAR(endog, dates=None, freq=None, missing='none')[source]¶

Fit VAR(p) process and do lag order selection

$y_t = A_1 y_{t-1} + \ldots + A_p y_{t-p} + u_t$

Parameters:

endog : array-like

2-d endogenous response variable. The independent variable.

dates : array-like

must match number of rows of endog

References

Lutkepohl (2005) New Introduction to Multiple Time Series Analysis

Methods

`fit`([maxlags, method, ic, trend, verbose])	Fit the VAR model
`predict`(params[, start, end, lags, trend])	Returns in-sample predictions or forecasts
`select_order`([maxlags, verbose])	Compute lag order selections based on each of the available information

Attributes

`endog_names`
`exog_names`