Results 31 to 40 of about 174,249,668 (304)

Strong Law of Large Numbers of Pettis-Integrable Multifunctions

open access: yesJournal of Mathematics, 2019
Using reversed martingale techniques, we prove the strong law of large numbres for independent Pettis-integrable multifunctions with convex weakly compact values in a Banach space.
Hamid Oulghazi, Fatima Ezzaki
doaj   +1 more source

Strong laws of large numbers for general random variables in sublinear expectation spaces

open access: yesJournal of Inequalities and Applications, 2019
In this paper, we obtain the equivalent relations between Kolmogorov maximal inequality and Hájek–Rényi maximal inequality both in moment and capacity types in sublinear expectation spaces.
Weihuan Huang, Panyu Wu
doaj   +1 more source

Further Spitzer’s law for widely orthant dependent random variables

open access: yesJournal of Inequalities and Applications, 2021
The Spitzer’s law is obtained for the maximum partial sums of widely orthant dependent random variables under more optimal moment conditions.
Pingyan Chen, Jingjing Luo, Soo Hak Sung
doaj   +1 more source

Concentration inequalities for upper probabilities

open access: yesJournal of Inequalities and Applications, 2020
In this paper, we obtain a Bernstein-type concentration inequality and McDiarmid’s inequality under upper probabilities for exponential independent random variables.
Yuzhen Tan
doaj   +1 more source

On the Strong Law of Large Numbers [PDF]

open access: yesTransactions of the American Mathematical Society, 1949
\(f(x) = f(x+1)\) besitze in \((0,1)\) den Mittelwert Null sowie die Streuung Eins und \((n_k)\) sei eine Folge von natürlichen Zahlen mit \(n_{k+1}/n_k > c > 1\). Die Frage, welche Bedingung das sog. starke Gesetz \[ g = \lim_{N\to \infty} \sum_{k=1}^N f(n_k x)/N = 0 \] für fast alle \(x\) sichert, ist von Kac, Salem, Zygmund unlängst mit den \(n ...
openaire   +1 more source

On Some Conditions for Strong Law of Large Numbers for Weighted Sums of END Random Variables under Sublinear Expectations

open access: yesDiscrete Dynamics in Nature and Society, 2019
In this article, we research some conditions for strong law of large numbers (SLLNs) for weighted sums of extended negatively dependent (END) random variables under sublinear expectation space.
Xiaochen Ma, Qunying Wu
doaj   +1 more source

A Strong Law of Large Numbers for Super-stable Processes. [PDF]

open access: yes, 2014
Let ℓ be Lebesgue measure and X=(Xt,t≥0;Pμ) be a supercritical, super-stable process corresponding to the operator −(−Δ)α/2u+βu−ηu2 on Rd with constants β,η>0 and α∈(0,2]. Put View the MathML source, which for each smallθ is an a.s. convergent complex-
Kouritzin, Michael, Ren, Y.-X.
core   +1 more source

Convergence properties for coordinatewise asymptotically negatively associated random vectors in Hilbert space

open access: yesOpen Mathematics, 2023
In this work, the authors study some convergence results including weak law of large numbers, strong law of large numbers, complete convergence, and complete moment convergence for weighted sums of coordinatewise asymptotically negatively associated ...
He Qihui, Pan Lin
doaj   +1 more source

Some limit theorems for weighted negative quadrant dependent random variables with infinite mean

open access: yesJournal of Inequalities and Applications, 2018
In the present paper, we will investigate weak laws of large numbers for weighted pairwise NQD random variables with infinite mean. The almost sure upper and lower bounds for a particular normalized weighted sum of pairwise NQD nonnegative random ...
Fuqiang Ma, Jianmin Li, Tiantian Hou
doaj   +1 more source

Some limit properties for a hidden inhomogeneous Markov chain

open access: yesJournal of Inequalities and Applications, 2018
This paper presents a general strong limit theorem for delayed sum of functions of random variables for a hidden time inhomogeneous Markov chain (HTIMC), and as corollaries, some strong laws of large numbers for HTIMC are established thereby.
Yun Dong, Fang-qing Ding, Qi-feng Yao
doaj   +1 more source

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