Multivariate, group Lasso

Groups the series based on the lags of the explanatory variables. The model selects the variables and their lags based on lag grouping, meaning that the 1st…

Sparse refers to not penalizing a whole group. In certain scenarios, a group penalty can be too restrictive. On the other hand, having many groups will…

In this model the grouping distinguishes between a series’ own lags and those of other series. This structure is similar to Componentwise (see below) but…

VARX Endegenous-First utilizes a penalty to prioritize endogenous series. At a given lag, an exogenous series can enter the model only if their endogenous…

Consists of a Lasso penalty that increases geometrically with lag. This means that shorter lags are prioritized in these models, compared to the set up in…