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SPECTRAL RADIUS,KRONECKER PRODUCTS AND STATIONARITY
Authors:Jian Liu
Abstract:Abstract. We provide a stochastic proof of the inequality ρ(A?A+B?B) ≥ρ(A?A), where ρ(M) denotes the spectral radius of any square matrix M, i.e. max{|eigenvalues| of M}, and M?N denotes the Kronecker product of any two matrices M and N. The inequality is then used to show that stationarity of the bilinear model image will imply stationarity of the linear part, i.e. the linear ARMA model image for r= 1 and q= 1. Furthermore, it is shown that stationarity of the subdiagonal model, i.e. the bilinear model with bij=0 for i< j, again implies stationarity of its linear part, provided that the stationarity condition given by Bhaskara Rao and his colleagues is met. Interestingly, the conclusion that stationarity of the subdiagonal models, implies that the linear component models cannot be extended to the general non-subdiagonal bilinear models. The last observation is demonstrated via a simple example with p=m= 1, r= 0 and q= 2.
Keywords:Spectral radius  Kronecker product  stationarity  bilinear model  subdiagonal model  Yule-Walker estimation procedure  ARMA model
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