In this chapter, a procedure is presented to use the bootstrap in choosing the best approximation in terms of forecasting performance for the equivalent state-space representation of a vector autoregressive model. It is found that the proposed procedure, which uses each approximant's forecasting...

In this chapter, a vector subset autoregressive process is fitted using a block modified Choleski decomposition method and a leaps-and-bounds algorithm to attain the best subset autoregression for each size (number of non-zero coefficient matrices). Model selection criteria are then employed to...