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1.
Fu Qing GAO 《数学学报(英文版)》2007,23(8):1527-1536
Let {Xn;n≥ 1} be a sequence of independent non-negative random variables with common distribution function F having extended regularly varying tail and finite mean μ = E(X1) and let {N(t); t ≥0} be a random process taking non-negative integer values with finite mean λ(t) = E(N(t)) and independent of {Xn; n ≥1}. In this paper, asymptotic expressions of P((X1 +… +XN(t)) -λ(t)μ 〉 x) uniformly for x ∈[γb(t), ∞) are obtained, where γ〉 0 and b(t) can be taken to be a positive function with limt→∞ b(t)/λ(t) = 0. 相似文献
2.
??In this paper, precise large deviations of nonnegative,
non-identical distributions and negatively associated random variables are investigated.
Under certain conditions, the lower bound of the precise large deviations for the
non-random sum is solved and the uniformly asymptotic results for the corresponding
random sum are obtained. At the same time, we deeply discussed the compound renewal
risk model, in which we found that the compound renewal risk model can be equivalent
to renewal risk model under certain conditions. The relative research results of
precise large deviations are applied to the more practical compound renewal risk model,
and the theoretical and practical values are verified. In addition, this paper also
shows that the impact of this dependency relationship between random variables to
precise large deviations of the final result is not significant. 相似文献
3.
进一步研究随机变量部分和与随机和的大偏差,其中S(n)=∑ni=1Xi,S(t)=∑N(t)i=1Xi(t>0).{Xn,n≥1}是一个独立同分布的随机变量(未必是非负的)序列具有共同的分布F(定义于R上)和有限期望μ=EX1.{N(t),t≥0}是一个非负的整数值的随机变量的更新计数过程且与{Xn,n≥1}相互独立.本文在假定F∈C条件下,进一步推广并改进了由Klüppelberg等和Kaiw等人给出的一些大偏差结果.这些结果可应用到某些金融保险方面的一些特定的问题中去. 相似文献
4.
本文得到次线性期望下独立同分布的随机变量的样本轨道大偏差. 在次线性期望下所得的结果推广了概率空间的相应结果. 相似文献
5.
In this paper, we study the case of independent sums in multi-risk model. Assume that there exist k types of variables. The ith are denoted by {Xij, j ≥ 1}, which are i.i.d.with common density function fi(x) ∈ OR and finite mean, i = 1,..., k. We investigate local large deviations for partial sums k i=1Sni= k i=1 nij=1Xij. 相似文献
6.
Let X
1, X
2,... be a sequence of i.i.d. non-negative random variables with heavy tails. W e study logarithmic asymptotics for the distributions of the partial sums S
n
= X
1 + ··· + X
n
. Our main interest is in the crude estimates P(S
n
> n
x
) n
–x + 1 for appropriate values of x where is a specific parameter. The related conjecture proposed by Gantert (Stat. Probab. Lett. 49, 113–118) is investigated. 相似文献
7.
Leonas Saulis 《Acta Appl Math》1999,58(1-3):291-310
The work is designated for obtaining asymptotic expansions and determination of structures of the remainder terms that take into consideration large deviations both in Cramer zones and Linnik power zones for the distribution function of sums of independent nonidentically distributed random variables (r.v.). In this scheme of summation of r.v., the results are obtained first by mainly using the general lemma on large deviations considering asymptotic expansions for an arbitrary r.v. with regular behaviour of its cumulants [11]. Asymptotic expansions in the Cramer zone for the distribution function of sums of identically distributed r.v. were investigated in the works [1,2]. Note that asymptotic expansions for large deviations were first obtained in the probability theory by J. Kubilius [3]. 相似文献
8.
9.
This paper is a further investigation into the large deviations for random sums of heavy-tailed,we extended and improved some results in ref. [1] and [2]. These results can applied to some questions in Insurance and Finance. 相似文献
10.
This paper is a further investigation of large deviations for sums of random variables S_n=sum form i=1 to n X_i and S(t)=sum form i=1 to N(t) X_i,(t≥0), where {X_n,n≥1) are independent identically distribution and non-negative random variables, and {N(t),t≥0} is a counting process of non-negative integer-valued random variables, independent of {X_n,n≥1}. In this paper, under the suppose F∈G, which is a bigger heavy-tailed class than C, proved large deviation results for sums of random variables. 相似文献
11.
Let {X, X_k : k ≥ 1} be a sequence of independent and identically distributed random variables with a common distribution F. In this paper, the authors establish some results on the local precise large and moderate deviation probabilities for partial sums S_n =sum from i=1 to n(X_i) in a unified form in which X may be a random variable of an arbitrary type,which state that under some suitable conditions, for some constants T 0, a and τ 1/2and for every fixed γ 0, the relation P(S_n- na ∈(x, x + T ]) ~nF((x + a, x + a + T ]) holds uniformly for all x ≥γn~τ as n→∞, that is, P(Sn- na ∈(x, x + T ]) lim sup- 1 = 0.n→+∞x≥γnτnF((x + a, x + a + T ])The authors also discuss the case where X has an infinite mean. 相似文献
12.
Bao Zhen-hua 《东北数学》2009,25(3):223-230
In this paper, we study the precise large deviations for the prospectiveloss process with consistently varying tails. The obtained results improve some related known ones. 相似文献
13.
14.
15.
16.
Large Deviations of Heavy-Tailed Sums with Applications in Insurance 总被引:13,自引:0,他引:13
First we give a short review of large deviation results for sums of i.i.d. random variables. The main emphasis is on heavy-tailed
distributions. We stress more the methodology than the detailed calculations. Large deviation techniques are then applied
to randomly indexed sums and shot noise processes. We also indicate the close relationship between large deviation results
and the modeling of large insurance claims.
This revised version was published online in July 2006 with corrections to the Cover Date. 相似文献
17.
在负象限相依结构下,得到了支撵在(-∞,∞)上的(D)族随机变量非中心化以及中心化部分和的精致大偏差.同时,还在较弱的条件下,得到了相应的中心化随机和的精致大偏差. 相似文献
18.
在负象限相依结构下, 得到了支撑在 (-∞,∞) 上的 D 族随机变量非中心化以及中心化部分和的精致大偏差. 同时, 还在较弱的条件下, 得到了相应的中心化随机和的精致大偏差. 相似文献
19.
邱德华 《数学的实践与认识》2009,39(9)
利用Rosenthal型最大值不等式,得到了NA随机变量加权和的Marcinkiewicz-Zygmund强大数定律和完全收敛性,所获结果推广和改进了一些文献中相应的结果. 相似文献
20.
Let X,X
n
;n1 be a sequence of real-valued i.i.d. random variables with E(X)=0. Assume B(u) is positive, strictly increasing and regularly-varying at infinity with index 1/2<1. Set b
n
=B(n),n1. If
and
for some [0,), then it is shown that
and
for every real triangular array (a
n,k
;1kn,n1) and every array of bounded real-valued i.i.d. random variables W,W
n,k
;1kn,n1`` independent of {X,X
n
;n1}, where (W)=(E(W–E(W))2)1/2. An analogous law of the iterated logarithm for the unweighted sums
n
k=1
X
k
;n1} is also given, along with some illustrative examples. 相似文献