A strong law of large numbers for triangular mixingale arrays
In this paper a strong law of large numbers for triangular mixingale arrays is proven. The mixingale condition is one of asymptotically weak dependence. A strong law of large numbers for triangular mixingale arrays has not been established previously in the literature. The result is applied to kernel regression function estimation.
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Volume (Year): 27 (1996)
Issue (Month): 1 (March)
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References listed on IDEAS
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- Andrews, Donald W. K., 1987.
"Laws of Large Numbers for Dependent Non-Identically Distributed Random Variables,"
645, California Institute of Technology, Division of the Humanities and Social Sciences.
- Andrews, Donald W.K., 1988. "Laws of Large Numbers for Dependent Non-Identically Distributed Random Variables," Econometric Theory, Cambridge University Press, vol. 4(03), pages 458-467, December.
- de Jong, R.M., 1995. "Laws of Large Numbers for Dependent Heterogeneous Processes," Econometric Theory, Cambridge University Press, vol. 11(02), pages 347-358, February.
- Davidson, James, 1993. "An L1-convergence theorem for heterogeneous mixingale arrays with trending moments," Statistics & Probability Letters, Elsevier, vol. 16(4), pages 301-304, March.
- Hansen, Bruce E., 1991. "Strong Laws for Dependent Heterogeneous Processes," Econometric Theory, Cambridge University Press, vol. 7(02), pages 213-221, June.
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