scholarly journals Precise asymptotics in the deviation probability series of self-normalized sums

2011 ◽  
Vol 376 (1) ◽  
pp. 136-153 ◽  
Author(s):  
Dianliang Deng
2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Mingzhou Xu ◽  
Kun Cheng

By an inequality of partial sum and uniform convergence of the central limit theorem under sublinear expectations, we establish precise asymptotics in the law of the iterated logarithm for independent and identically distributed random variables under sublinear expectations.


2006 ◽  
Vol 58 (5) ◽  
pp. 1026-1094
Author(s):  
David Handelman

AbstractConnections between behaviour of real analytic functions (with no negative Maclaurin series coefficients and radius of convergence one) on the open unit interval, and to a lesser extent on arcs of the unit circle, are explored, beginning with Karamata's approach. We develop conditions under which the asymptotics of the coefficients are related to the values of the function near 1; specifically, a(n) ∼ f(1 – 1/n)/αn (for some positive constant α), where f(t) = Σa(n)tn. In particular, if F = Σc(n)tn where c(n) ≥ 0 and Σc(n) = 1, then f defined as (1 – F)–1 (the renewal or Green's function for F) satisfies this condition if F′ does (and a minor additional condition is satisfied). In come cases, we can show that the absolute sum of the differences of consecutiveMaclaurin coefficients converges. We also investigate situations in which less precise asymptotics are available.


2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Qunying Wu

The aim of this paper is to study and establish the precise asymptotics for complete integral convergence theorems under a sublinear expectation space. As applications, the precise asymptotics for p0≤p≤2 order complete integral convergence theorems have been generalized to the sublinear expectation space context. We extend some precise asymptotics for complete moment convergence theorems from the traditional probability space to the sublinear expectation space. Our results generalize corresponding results obtained by Liu and Lin (2006). There is no report on the precise asymptotics under sublinear expectation, and we provide the method to study this subject.


2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Guodong Xing ◽  
Shanchao Yang

The exponential inequality for weighted sums of a class of linearly negative quadrant dependent random variables is established, which extends and improves the corresponding ones obtained by Ko et al. (2007) and Jabbari et al. (2009). In addition, we also give the relevant precise asymptotics.


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