Strong laws for weighted sums of random variables satisfying generalized Rosenthal type inequalities

DOI10.1186/s13660-020-02311-1zbMath1503.60040OpenAlexW3032612972MaRDI QIDQ2069317

Yanchun Yi, Soo Hak Sung, Ping Yan Chen

Publication date: 20 January 2022

Published in: Journal of Inequalities and Applications (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1186/s13660-020-02311-1

zbMATH Keywords

strong law of large numbersweighted sumwidely orthant dependent random variable

Mathematics Subject Classification ID

Inequalities; stochastic orderings (60E15) Nonparametric estimation (62G05) Strong limit theorems (60F15) Functional limit theorems; invariance principles (60F17)

Related Items (7)

Capacity inequalities and strong laws for \(m\)-widely acceptable random variables under sub-linear expectations ⋮ Complete q-th moment convergence for the maximum of partial sums of m-negatively associated random variables and its application to the EV regression model^* ⋮ Marcinkiewicz–Zygmund type strong law of large numbers for weighted sums of random variables with infinite moment and its applications ⋮ Strong consistency of least-squares estimators in the simple linear errors-in-variables regression model with widely orthant dependent random variables ⋮ Weak convergence for weighted sums of a class of random variables with related statistical applications ⋮ Strong convergence for weighted sums of WOD random variables and its application in the EV regression model. ⋮ Strong consistency of LS estimators in simple linear EV regression models with WOD errors

Cites Work

• Unnamed Item
• Unnamed Item
• On complete convergence for weighted sums of \(\varphi \)-mixing random variables
• A comparison theorem on moment inequalities between negatively associated and independent random variables
• Weighted version of strong law of large numbers for a class of random variables and its applications
• Maximal inequalities and an invariance principle for a class of weakly dependent random variables
• A strong law for weighted sums of i.i.d. random variables
• Uniform asymptotics for the finite-time ruin probability of a dependent risk model with a constant interest rate
• A strong limit theorem for weighted sums of sequences of negatively dependent random variables
• Marcinkiewicz strong laws for linear statistics
• A Spitzer-type law of large numbers for widely orthant dependent random variables
• Limiting behavior of weighted sums of i.i.d. random variables
• On the subspaces of \(L^p\) \((p > 2)\) spanned by sequences of independent random variables

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