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The Central Limit Theorem for Globally Nonstationary Near-Epoch Dependent Functions of Mixing Processes: The Asymptotically Degenerate Case

Published online by Cambridge University Press:  11 February 2009

James Davidson
Affiliation:
London School of Economics

Abstract

The central limit theorem in Davidson [2] is extended to allow cases where the variances of sequence coordinates can be tending to zero. A trade-off is demonstrated between the degree of dependence and the rate of degeneration. For the martingale difference case, it is sufficient for the sum of the variances to diverge at the rate of log n.

Type
Articles
Copyright
Copyright © Cambridge University Press 1993

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References

1.Andrews, Donald W.K.Laws of large numbers for dependent non-identically distributed random variables. Econometric Theory 4 (1988): 458467.CrossRefGoogle Scholar
2.Davidson, James. A central limit theorem for globally nonstationary near-epoch dependent functions of mixing processes. Econometric Theory 8 (1992): 313329.CrossRefGoogle Scholar
3.Davidson, James. An L 1-convergence theorem for heterogeneous mixingale arrays with trending moments. Statistics and Probability Letters 17 (1993): to appear.Google Scholar
4.Gallant, A. Ronald. Nonlinear Statistical Models. New York: Wiley, 1987.CrossRefGoogle Scholar
5.Gallant, A. Ronald & Halbert, White. A Unified Theory of Estimation and Inference for Nonlinear Dynamic Models. Basil Blackwell, 1988.Google Scholar
6.McLeish, D.L.Dependent central limit theorems and invariance principles. Annals of Probability 2 (1974): 620628.CrossRefGoogle Scholar
7.McLeish, D.L.A maximal inequality and dependent strong laws. Annals of Probability 3 (1975): 329839.CrossRefGoogle Scholar
8.McLeish, D.L.Invariance principles for dependent variables. Z. Wahrscheinlichkeitstheorie verw. Gebeite 32 (1975): 165178.CrossRefGoogle Scholar
9.McLeish, D.L.On the invariance principle for nonstationary mixingales. Annals of Probability 5 (1977): 616621.CrossRefGoogle Scholar