Moment bounds for mixing random variables useful in nonparametric function estimation

Dennis D. Cox and Tae Yoon Kim

Stochastic Processes and their Applications, 1995, vol. 56, issue 1, 151-158

Abstract: Bounds for even moments of sums of strong mixing random variables are given which extend existing bounds. The method of proof uses simple facts about strong mixing random variables and combinatorial methods. The bound is particularly useful for triangular arrays with entries decreasing in size. To illustrate this, applications are being discussed to nonparametric kernel estimation with dependent observations.

Keywords: Moment; bounds; Strong; mixing; processes; Nonparametric; kernel; estimation (search for similar items in EconPapers)
Date: 1995
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Citations: View citations in EconPapers (17)

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