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Published September 11, 2017 | Submitted
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Laws of Large Numbers for Dependent Non-Identically Distributed Random Variables

Abstract

This paper provides L` and weak laws of large numbers for uniformly integrable L1-mixingales. The L1-mixingale condition is a condition of asymptotic weak temporal dependence that is weaker than most conditions considered in the literature. Processes covered by the laws of large numbers include martingale difference, Φ(.), ρ(.) and α(•) mixing, autoregressive moving average, infinite order moving average, near epoch dependent, L1-near epoch dependent, and mixingale sequences and triangular arrays. The random variables need not possess more than one moment finite and the L1-mixingale numbers need not decay to zero at any particular rate. The proof of the results is remarkably simple and completely self-contained.

Additional Information

I would like to thank the California Institute of Technology for their hospitality while this research was undertaken and the Alfred P. Sloan Foundation and the National Science Foundation for their financial support through a Research Fellowship and grant number SES-8618617, respectively.

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Created:
August 19, 2023
Modified:
January 14, 2024