Abstract

Abstract In the present paper, the sufficient and necessary conditions of the complete convergence and complete moment convergence for ρ͠-mixing random variables are established, which extend some well-known results.

Highlights

  • In the present paper, the su cient and necessary conditions of the complete convergence and complete moment convergence for ρ-mixing random variables are established, which extend some wellknown results

  • The notion of ρ-mixing random variables was rst introduced by Bradley [1], and a number of limits results for ρ-mixing random variables have been established by many authors

  • One can refer to Bradley [1] for the central limit theorem; Sung [2, 3], An and Yuan [4], Lan [5], Guo and Zhu [6] for complete convergence; Zhang [7] for complete moment convergence; Peligrad and Gut [8], Utev and Peligrad [9] for the moment inequalities; Gan [10], Wu and Jiang [11], Kuczmaszewska [12] for strong law of large numbers

Read more

Summary

Introduction

Let (Ω, F, P) be a probability space, {Xn , n ≥ } be a sequence of random variables de ned on (Ω, F, P), n. De ne the ρ-mixing coe cients by ρn = sup{ρ(FS , FT) : S, T ⊂ N with dist(S, T) ≥ n},. The sequence {Xn , n ≥ } is called ρ-mixing if there exists k ∈ N such that ρk

This work is licensed under the Creative Commons Attribution alone
Main results
Proofs of Main results
Xi ε n α
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call