广义复合二项风险模型的若干大偏差结果

This paper is a further investigation of large deviation for partial and random sums of random variables, where {Xn,n ≥ 1} is non-negative independent identically distributed random variables with a common heavy-tailed distribution function F on the real line R and finite mean μ∈ R. {N（n）,n ≥ 0} is a binomial process with a parameter p ∈ （0,1） and independent of {Xn,n ≥ 1}; {M（n）,n ≥ 0} is a Poisson process with intensity λ 〉 0, Sn = ΣNn i=1 Xi-cM（n）. Suppose F ∈ C, we futher extend and improve some large deviation results. These results can apply to certain problems in insurance and finance.

Some Large Deviation Results for Generalized Compound Binomial Risk Models

This paper is a further investigation of large deviation for partial and random sums of random variables, where $\{X_{n},n\geq 1\}$ is non-negative independent identically distributed random variables with a common heavy-tailed distribution function $F$ on the real line $R$ and finite mean $\mu\in R$. $\{N(n),n\geq 0\}$ is a binomial process with a parameter $p\in(0,1)$ and independent of $\{X_{n},n\geq 1\}$; $\{M(n),n\geq 0\}$ is a Poisson process with intensity $\lambda>0$, $S_{n}=\sum_{i=1}^{N(n)}X_{i}-cM(n)$. Suppose $F\in C$, we futher extend and improve some large deviation results. These results can apply to certain problems in insurance and finance.