期刊文献+
共找到4篇文章
< 1 >
每页显示 20 50 100
连续型指数差分布 被引量:1
1
作者 丁勇 《数理统计与管理》 CSSCI 北大核心 2006年第3期346-350,共5页
本文提出了一个连续型随机变量的概率分布:指数差分布。讨论了该分布的极值、拐点、数学期望和方差,推导了参数的矩估计公式,探讨了该分布与指数分布的关系,给出了该分布在药代动力学中的应用。
关键词 指数差分布 数学期望 指数分布 药代动力学
下载PDF
离散型指数差分布
2
作者 丁一飞 《数理统计与管理》 CSSCI 北大核心 2006年第5期530-535,共6页
本文提出了一个离散型概率分布:指数差分布,推导了该分布的最可能成功次数、数学期望和方差,探讨了该分布与几何分布的关系,给出了该分布在马尔可夫链模型中的应用。
关键词 指数差分布 数学期望 几何分布 马尔可夫链
下载PDF
Precise large deviation result for heavy-tailed random sums and applications to risk theory
3
作者 杨洋 林金官 《Journal of Southeast University(English Edition)》 EI CAS 2010年第3期498-501,共4页
The differences between two sequences of nonnegative independent and identically distributed random variables with sub-exponential tails and the random index are studied. The random index is a strictly stationary rene... The differences between two sequences of nonnegative independent and identically distributed random variables with sub-exponential tails and the random index are studied. The random index is a strictly stationary renewal counting process generated by some negatively associated random variables. Using a revised large deviation result of partial sums, the elementary renewal theorem and the central limit theorem of negatively associated random variables, a precise large deviation result is derived for the random sums. The result is applied to the customer-arrival-based insurance risk model. Some uniform asymptotics for the ruin probabilities of an insurance company are obtained as the number of customers or the time tends to infinity. 展开更多
关键词 precise large deviation random sum sub-exponential distribution renewal counting process customer-arrival-based insurance risk model
下载PDF
Large Deviations for Sums of Heavy-tailed Random Variables
4
作者 郭晓燕 孔繁超 《Chinese Quarterly Journal of Mathematics》 CSCD 北大核心 2007年第2期282-289,共8页
This paper is a further investigation of large deviations for sums of random variables Sn=i=1∑n Xi and S(t)=i=1∑N(t)Xi,(t≥0), where {X_n,n≥1) are independent identically distribution and non-negative random... This paper is a further investigation of large deviations for sums of random variables Sn=i=1∑n Xi and S(t)=i=1∑N(t)Xi,(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. 展开更多
关键词 large deviation heavy-tailed distribution strongly subexponential distribution lognormal distribution
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部