Results 51 to 60 of about 1,203 (134)

A strong law of large numbers for independent compactly uniformly integrable random sets [PDF]

Arab Journal of Mathematical Sciences
PurposeThe aim of this work is to prove a strong law of large numbers for a sequence of independent compactly uniformly integrable random sets with values in the family of convex closed subsets of a separable Banach space E, again without requiring any ...
Mohammed El Allali, El-Moustafid Mohamed, Fatima Ezzaki   +2 more
doaj   +1 more source

The law of the iterated logarithm for exchangeable random variables

International Journal of Mathematics and Mathematical Sciences, Volume 18, Issue 2, Page 391-396, 1995., 1993
In this note, necessary and sufficient conditions for laws of the iterated logarithm are developed for exchangeable random variables.
Hu-Ming Zhang, Robert L. Taylor
wiley   +1 more source

Strong convergence for weighted sums of (α, β)-mixing random variables and application to simple linear EV regression model

Open Mathematics
In this article, the complete convergence and the Kolmogorov strong law of large numbers for weighted sums of (α,β)\left(\alpha ,\beta )-mixing random variables are presented.
Hu Wenjing, Wang Wei, Wu Yi
doaj   +1 more source

On complete convergence in a Banach space

International Journal of Mathematics and Mathematical Sciences, Volume 17, Issue 1, Page 1-14, 1994., 1993
Sufficient conditions are given under which a sequence of independent random elements taking values in a Banach space satisfy the Hsu and Robbins law of large numbers. The complete convergence of random indexed sums of random elements is also considered.
Anna Kuczmaszewska, Dominik Szynal
wiley   +1 more source

Higher-order expansions for distributions of extremes from general error distribution

, 2014
In this short note, with optimal normalizing constants, the higher-order expansion for a distribution of normalized partial maximum from the general error distribution is derived, by which one deduces the associate convergence rate of the distribution of
Pu Jia, Tingting Li
semanticscholar   +1 more source

On Complete Moment Convergence for Randomly Weighted Sums of NSD Random Variables

Journal of Mathematical Study, 2019
In this paper, we investigate the complete moment convergence and complete convergence for randomly weighted sums of negatively superadditive dependent (NSD, in short) random variables. The results obtained in the paper generalize the convergence theorem
xiangmin Sun
semanticscholar   +1 more source

On Feller′s criterion for the law of the iterated logarithm

International Journal of Mathematics and Mathematical Sciences, Volume 17, Issue 2, Page 323-340, 1994., 1993
Combining Feller′s criterion with a non‐uniform estimate result in the context of the Central Limit Theorem for partial sums of independent random variables, we obtain several results on the Law of the Iterated Logarithm. Two of these results refine corresponding results of Wittmann (1985) and Egorov (1971). In addition, these results are compared with
Deli Li, M. Bhaskara Rao, Xiangchen Wang
wiley   +1 more source

Strong laws for weighted sums of widely orthant dependent random variables and applications

Open Mathematics
In this study, the strong law of large numbers and the convergence rate for weighted sums of non-identically distributed widely orthant dependent random variables are established.
Zhu Yong, Wang Wei, Chen Kan
doaj   +1 more source

An Almost Sure Central Limit Theorem for Self-normalized Weighted Sums of the ρ-mixing Random Variables

, 2016
In this paper, an almost sure central limit theorem is obtained for self-normalized weighted sums of the φ mixing random variables. Our results extend and give substantial improvement for the result obtained by Zhang [12] and our results also extend the ...
F. Feng, Dingcheng Wang, Qunying Wu
semanticscholar   +1 more source

Convergence rate of extremes from Maxwell sample

, 2013
For the partial maximum from a sequence of independent and identically distributed random variables with Maxwell distribution, we establish the uniform convergence rate of its distribution to the extreme value distribution.MSC:62E20, 60E05, 60F15, 60G15.
Chuandi Liu, Baogen Liu
semanticscholar   +1 more source