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Stationarity And Central Limit Theorem Associated With Bilinear Time Series Models

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  • Kamal C. Chanda

Abstract

. Consider the general bilinear times series model where {Xt; t= 0, L1, …} is a p‐variate process, C(p x (s+ 1)), A(p x p). Bt(p x p) (1 ≤j≤q) are arbitrary matrices of constants, εT=[εt,…εt‐q+1] and {εt; t=0, ±1, …} is a strictly stationary ergodic sequence of random variables. We investigate a set of minimal regularity conditions (on C, A, Bj and {εt}) under which we can establish the existence and causality of Xt and the asymptotic normality of the sample mean derived from {Xt}.

Suggested Citation

  • Kamal C. Chanda, 1991. "Stationarity And Central Limit Theorem Associated With Bilinear Time Series Models," Journal of Time Series Analysis, Wiley Blackwell, vol. 12(4), pages 301-313, July.
    • Handle: RePEc:bla:jtsera:v:12:y:1991:i:4:p:301-313
    DOI: 10.1111/j.1467-9892.1991.tb00085.x
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    Cited by:

    1. Kamal C. Chanda, 2005. "Large sample properties of spectral estimators for a class of stationary nonlinear processes," Journal of Time Series Analysis, Wiley Blackwell, vol. 26(1), pages 1-16, January.

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