DETERMINING THE ORDER OF A VECTOR AUTOREGRESSION WHEN THE NUMBER OF COMPONENT SERIES IS LARGE
对比了当分量序列数量很大时几种确定向量自回归阶数的方法的表现，发现其表现依赖于分量数、参数矩阵非零元素个数和阶数上限，并提出了一个新的多元阶数确定准则。
Abstract. We contrast the performance of several methods used for identifying the order of vector autoregressive (VAR) processes when the number K of component series is large. Through simulation experiments we show that their performance is dependent on K , the number of nonzero elements in the polynomial matrices of the VAR parameters and the permitted upper limit of the order used in testing the autoregressive structure. In addition we introduce a new quite powerful multivariate order determination criterion.