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The strong law of large numbers for weighted averages under dependence assumptions
Authors:Tapas K Chandra  Subhashis Ghosal
Institution:(1) Division of Theoretical Statistics and Mathematics, Indian Statistical Institute, 203 B. T. Road, 700035 Calcutta, India
Abstract:Strong laws of large numbers (SLLN) for weighted averages are proved under various dependence assumptions when the variables are not necessarily independent or identically distributed. The results considerably extend the existing results. Weighted versions of the Marcinkiewicz-Zygmund SLLN are also formulated and proved under a similar set up. It seems that such results are not known even for independent and identically distributed random variables.
Keywords:Asymptotically quadrant sub-independence  Marcinkiewicz-Zygmund strong laws  maximal inequalities  mixing conditions  mixingale difference  strong laws  weighted averages
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