Asymptotic Approximations of Ratio Moments Based on Dependent Sequences

Hongyan Fang, Saisai Ding, Xiaoqin Li and Wenzhi Yang
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Hongyan Fang: School of Mathematical Sciences, Anhui University, Hefei 230601, China
Saisai Ding: School of Mathematical Sciences, Anhui University, Hefei 230601, China
Xiaoqin Li: School of Mathematical Sciences, Anhui University, Hefei 230601, China
Wenzhi Yang: School of Mathematical Sciences, Anhui University, Hefei 230601, China

Mathematics, 2020, vol. 8, issue 3, 1-18

Abstract: The widely orthant dependent (WOD) sequences are very weak dependent sequences of random variables. For the weighted sums of non-negative m -WOD random variables, we provide asymptotic expressions for their appropriate inverse moments which are easy to calculate. As applications, we also obtain asymptotic expressions for the moments of random ratios. It is pointed out that our random ratios can include some models such as change-point detection. Last, some simulations are illustrated to test our results.

Keywords: asymptotic approximation; inverse moments; WOD random variables; ratio moments (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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