Abstract:

A class of latent ancestral graph for modelling the
dependence structure of structural vector autoregressive(VAR)
model affected by latent variables is proposed.The graphs are
mixed graphs with possibly two kind of edges,namely directed and
bidirected edges.The vertex set denotes random variables at dif-
ferent times.In Gaussian case,the latent ancestral graph leads to
a simple parameterization model.A modified iterative conditional
fitting algorithm is presented to obtain maximum likelihood esti-
mation of the parameters.Furthermore,a log-likelihood criterion
is used to select the most appropriate models.Simulations are
performed using illustrative examples and results are provided to
demonstrate the validity of the methods.